Bioinformatics Research and Applications: 16th International Symposium, ISBRA 2020, Moscow, Russia, December 1–4, 2020, Proceedings

The inference of mitochondrial haplogroups is an important step in forensic analysis of DNA samples collected at a crime scene. In this paper we introduced efficient inference algorithms based on Jaccard similarity between variants called from high-throughput sequencing data of such DNA samples and mutations collected in public databases such as PhyloTree. Experimental results on real and simulated datasets show that our mutation analysis methods have accuracy comparable to that of state-of-the-art methods based on haplogroup frequency estimation for both single-individual samples and two-individual mixtures, with a much lower running time.

[1]  Xiaojun Chen,et al.  Large-scale prediction of microRNA-disease associations by combinatorial prioritization algorithm , 2017, Scientific Reports.

[2]  Wing Hung Wong,et al.  SeqMap: mapping massive amount of oligonucleotides to the genome , 2008, Bioinform..

[3]  Colin Campbell,et al.  An integrative approach to predicting the functional effects of small indels in non-coding regions of the human genome , 2017, BMC Bioinformatics.

[4]  S. Gabriel,et al.  Discovery and saturation analysis of cancer genes across 21 tumor types , 2014, Nature.

[5]  Anil K. Jain,et al.  Data clustering: a review , 1999, CSUR.

[6]  M. Affolter,et al.  Homeodomain proteins: an update , 2015, Chromosoma.

[7]  T. Kivisild,et al.  Maternal ancestry and population history from whole mitochondrial genomes , 2015, Investigative Genetics.

[8]  Yong-Gang Yao,et al.  MitoTool: a web server for the analysis and retrieval of human mitochondrial DNA sequence variations. , 2011, Mitochondrion.

[9]  S. Schuster,et al.  Integrative analysis of environmental sequences using MEGAN4. , 2011, Genome research.

[10]  Koji Ishiya,et al.  MitoSuite: a graphical tool for human mitochondrial genome profiling in massive parallel sequencing , 2017, PeerJ.

[11]  Mong-Li Lee,et al.  Labeling network motifs in protein interactomes for protein function prediction , 2007, 2007 IEEE 23rd International Conference on Data Engineering.

[12]  Xiao Li,et al.  In Silico Prediction of Chemical Acute Oral Toxicity Using Multi-Classification Methods , 2014, J. Chem. Inf. Model..

[13]  Martin Dugas,et al.  RSVSim: an R/Bioconductor package for the simulation of structural variations , 2013, Bioinform..

[14]  Albert-László Barabási,et al.  Statistical mechanics of complex networks , 2001, ArXiv.

[15]  Daniel N. Baker,et al.  KrakenUniq: confident and fast metagenomics classification using unique k-mer counts , 2018, Genome Biology.

[16]  Falk Schreiber,et al.  Analysis of Biological Networks , 2008 .

[17]  Victor Kuzmin,et al.  Hierarchical QSAR technology based on the Simplex representation of molecular structure , 2008, J. Comput. Aided Mol. Des..

[18]  Erin K. Molloy,et al.  FastMulRFS: Statistically consistent polynomial time species tree estimation under gene duplication , 2019, bioRxiv.

[19]  Tongqing Zhou,et al.  Identification of a CD4-Binding-Site Antibody to HIV that Evolved Near-Pan Neutralization Breadth. , 2016, Immunity.

[20]  Anne Berger,et al.  Signet-ring cell carcinoma of the stomach: Impact on prognosis and specific therapeutic challenge. , 2015, World journal of gastroenterology.

[21]  A. Lavecchia Deep learning in drug discovery: opportunities, challenges and future prospects. , 2019, Drug discovery today.

[22]  Daniel Merkle,et al.  Chemical Graph Transformation with Stereo-Information , 2017, ICGT.

[23]  A. Zhang,et al.  Inferring species membership using DNA sequences with back-propagation neural networks. , 2008, Systematic biology.

[24]  J. Hermens,et al.  Electrophiles and acute toxicity to fish. , 1990, Environmental health perspectives.

[25]  Yoshihiro Yamanishi,et al.  Supervised prediction of drug–target interactions using bipartite local models , 2009, Bioinform..

[26]  J. Epstein,et al.  Isolation and characterization of a bat SARS-like coronavirus that uses the ACE2 receptor , 2013, Nature.

[27]  Michael R. Duchen,et al.  Mitochondria, calcium-dependent neuronal death and neurodegenerative disease , 2012, Pflügers Archiv - European Journal of Physiology.

[28]  Clara Fannjiang,et al.  A deep learning approach to pattern recognition for short DNA sequences , 2018, bioRxiv.

[29]  I. Măndoiu,et al.  Single cell RNA-seq data clustering using TF-IDF based methods , 2018, BMC Genomics.

[30]  Daniel J. Blankenberg,et al.  Galaxy: a platform for interactive large-scale genome analysis. , 2005, Genome research.

[31]  Matteo Comin,et al.  Beyond Fixed-Resolution Alignment-Free Measures for Mammalian Enhancers Sequence Comparison , 2014, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[32]  C. Vullo,et al.  The contributions of anthropology and mitochondrial DNA analysis to the identification of the human skeletal remains of the Australian outlaw Edward 'Ned' Kelly. , 2014, Forensic science international.

[33]  C. Woese,et al.  Bacterial evolution , 1987, Microbiological reviews.

[34]  H. Bussey,et al.  Large‐scale essential gene identification in Candida albicans and applications to antifungal drug discovery , 2003, Molecular microbiology.

[35]  Alexandre Varnek,et al.  Structural and Physico-Chemical Interpretation (SPCI) of QSAR Models and Its Comparison with Matched Molecular Pair Analysis , 2016, J. Chem. Inf. Model..

[36]  Jacob D. Durrant,et al.  AutoClickChem: Click Chemistry in Silico , 2012, PLoS Comput. Biol..

[37]  E. Marchiori,et al.  Predicting Drug-Target Interactions for New Drug Compounds Using a Weighted Nearest Neighbor Profile , 2013, PloS one.

[38]  Daniel P. Kennedy,et al.  The Autism Brain Imaging Data Exchange: Towards Large-Scale Evaluation of the Intrinsic Brain Architecture in Autism , 2013, Molecular Psychiatry.

[39]  D. Alland,et al.  A detailed analysis of 16S ribosomal RNA gene segments for the diagnosis of pathogenic bacteria. , 2007, Journal of microbiological methods.

[40]  Bauke Ylstra,et al.  Sequencing Structural Variants in Cancer for Precision Therapeutics. , 2016, Trends in genetics : TIG.

[41]  Robert Abel,et al.  OPLS3e: Extending Force Field Coverage for Drug-Like Small Molecules. , 2019, Journal of chemical theory and computation.

[42]  Tara N. Sainath,et al.  A Comparison of Sequence-to-Sequence Models for Speech Recognition , 2017, INTERSPEECH.

[43]  Joshua A. Grochow,et al.  Network Motif Discovery Using Subgraph Enumeration and Symmetry-Breaking , 2007, RECOMB.

[44]  Guillaume Lamoureux,et al.  Protein-protein docking using learned three-dimensional representations , 2019 .

[45]  Eugene Stepanov,et al.  Modeling conformational redox‐switch modulation of human succinic semialdehyde dehydrogenase , 2015, Proteins.

[46]  Luay Nakhleh,et al.  Species Tree Inference under the Multispecies Coalescent on Data with Paralogs is Accurate , 2018, bioRxiv.

[47]  J R Kremer,et al.  Computer visualization of three-dimensional image data using IMOD. , 1996, Journal of structural biology.

[48]  Jerzy Tiuryn,et al.  DLS-trees: A model of evolutionary scenarios , 2006, Theor. Comput. Sci..

[49]  Edwin Cuppen,et al.  Prioritization of genes driving congenital phenotypes of patients with de novo genomic structural variants , 2019, Genome Medicine.

[50]  Mathieu Coppey,et al.  Modelling the Bicoid gradient , 2010, Development.

[51]  N. DeLuca,et al.  Transcription of the Herpes Simplex Virus 1 Genome during Productive and Quiescent Infection of Neuronal and Nonneuronal Cells , 2014, Journal of Virology.

[52]  J. Berkson Application of the Logistic Function to Bio-Assay , 1944 .

[53]  Rolf Altenburger,et al.  Structural alerts--a new classification model to discriminate excess toxicity from narcotic effect levels of organic compounds in the acute daphnid assay. , 2005, Chemical research in toxicology.

[54]  D. J. Wheeler,et al.  A Block-sorting Lossless Data Compression Algorithm , 1994 .

[55]  Stefan Schouten,et al.  Comparison of the effect of salinity on the D/H ratio of fatty acids of heterotrophic and photoautotrophic microorganisms. , 2015, FEMS microbiology letters.

[56]  Jie Liu,et al.  ClusterMI: Detecting High-Order SNP Interactions Based on Clustering and Mutual Information , 2018, International journal of molecular sciences.

[57]  Roberto J. Bayardo,et al.  Scaling up all pairs similarity search , 2007, WWW '07.

[58]  Renmin Han,et al.  A novel fully automatic scheme for fiducial marker-based alignment in electron tomography. , 2015, Journal of structural biology.

[59]  Xi Zhang,et al.  An Obstructive Sleep Apnea Detection Approach Using a Discriminative Hidden Markov Model From ECG Signals , 2016, IEEE Transactions on Biomedical Engineering.

[60]  A. Gonzalez-Perez,et al.  Improving the prediction of the functional impact of cancer mutations by baseline tolerance transformation , 2012, Genome Medicine.

[61]  Vincenza Rita Lo Vasco,et al.  Phosphoinositide pathway and the signal transduction network in neural development , 2012, Neuroscience Bulletin.

[62]  C. Sander,et al.  Target mRNA abundance dilutes microRNA and siRNA activity , 2010, Molecular systems biology.

[63]  Q. Cui,et al.  An Analysis of Human MicroRNA and Disease Associations , 2008, PloS one.

[64]  Yuan Zhou,et al.  HMDD v3.0: a database for experimentally supported human microRNA–disease associations , 2018, Nucleic Acids Res..

[65]  Young Do Kwon,et al.  Synthesis, Antiviral Potency, in Vitro ADMET, and X-ray Structure of Potent CD4 Mimics as Entry Inhibitors That Target the Phe43 Cavity of HIV-1 gp120. , 2017, Journal of medicinal chemistry.

[66]  Chee Keong Kwoh,et al.  QuickVina: Accelerating AutoDock Vina Using Gradient-Based Heuristics for Global Optimization , 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[67]  J. Aubé,et al.  Butitaxel analogues: synthesis and structure-activity relationships. , 1997, Journal of medicinal chemistry.

[68]  Min Li,et al.  Protein-protein interaction site prediction through combining local and global features with deep neural networks , 2019, Bioinform..

[69]  Peter E. Hart,et al.  Nearest neighbor pattern classification , 1967, IEEE Trans. Inf. Theory.

[70]  Matteo Comin,et al.  Fast and Sensitive Classification of Short Metagenomic Reads with SKraken , 2017, BIOSTEC.

[71]  John Collinge,et al.  Structural Variation in Amyloid-β Fibrils from Alzheimer’s Disease Clinical Subtypes , 2016, Nature.

[72]  Jinjun Xiong,et al.  Decoupled Classification Refinement: Hard False Positive Suppression for Object Detection , 2018, ArXiv.

[73]  S. Leibler,et al.  Establishment of developmental precision and proportions in the early Drosophila embryo , 2002, Nature.

[74]  Genki Terashi,et al.  Classification in Cryo-Electron Tomograms , 2019, 3DOR@Eurographics.

[75]  Tien Huynh,et al.  NemoMap: Improved Motif-centric Network Motif Discovery Algorithm , 2018, Advances in Science, Technology and Engineering Systems Journal.

[76]  Günther Specht,et al.  HaploGrep: a fast and reliable algorithm for automatic classification of mitochondrial DNA haplogroups , 2011, Human mutation.

[77]  E. Koonin Orthologs, paralogs, and evolutionary genomics. , 2005, Annual review of genetics.

[78]  Lukman Thalib,et al.  Prevalence of BRCA mutations among hereditary breast and/or ovarian cancer patients in Arab countries: systematic review and meta-analysis , 2019, BMC Cancer.

[79]  S. Raghavan,et al.  Snaps and mends: DNA breaks and chromosomal translocations , 2015, The FEBS journal.

[80]  Chris H. Q. Ding,et al.  Convex and Semi-Nonnegative Matrix Factorizations , 2010, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[81]  David Fern'andez-Baca,et al.  Checking Phylogenetic Decisiveness in Theory and in Practice , 2020, ISBRA.

[82]  Thomas Meitinger,et al.  Biallelic Mutations in NBAS Cause Recurrent Acute Liver Failure with Onset in Infancy , 2015, American journal of human genetics.

[83]  Alexander Spirov,et al.  Formation of the bicoid morphogen gradient: an mRNA gradient dictates the protein gradient , 2009, Development.

[84]  Igor A. Khalymbadzha,et al.  15N labeling and analysis of 13C–15N and 1H–15N couplings in studies of the structures and chemical transformations of nitrogen heterocycles , 2019, RSC advances.

[85]  S. Saitta,et al.  MAP'ing CNS Development and Cognition: An ERKsome Process , 2009, Neuron.

[86]  International Human Genome Sequencing Consortium Initial sequencing and analysis of the human genome , 2001, Nature.

[87]  Xinchen Wang,et al.  Tissue-specific alternative splicing remodels protein-protein interaction networks. , 2012, Molecular cell.

[88]  Le Song,et al.  PGCN: Disease gene prioritization by disease and gene embedding through graph convolutional neural networks , 2019, bioRxiv.

[89]  M. Lynch,et al.  The evolutionary fate and consequences of duplicate genes. , 2000, Science.

[90]  Ben Glocker,et al.  Spectral Graph Convolutions for Population-based Disease Prediction , 2017, MICCAI.

[91]  Jean-Eric Pin,et al.  Algorithms for computing finite semigroups , 1997 .

[92]  P. Pandolfi,et al.  The multilayered complexity of ceRNA crosstalk and competition , 2014, Nature.

[93]  Patrick Haffner,et al.  Support vector machines for histogram-based image classification , 1999, IEEE Trans. Neural Networks.

[94]  Attila Egri-Nagy,et al.  Applications of Automata Theory and Algebra via the Mathematical Theory of Complexity to Biology, Physics, Psychology, Philosophy, and Games. John Rhodes. Chrystopher L. Nehaniv (Ed.). Foreword by Morris W. Hirsch. (2009, World Scientific Books.) ISBN: 978-981-283-696-0, US$65 (hardcover); ISBN: 978 , 2011, Artificial Life.

[95]  Xi Zhang,et al.  An Automatic Screening Approach for Obstructive Sleep Apnea Diagnosis Based on Single-Lead Electrocardiogram , 2015, IEEE Transactions on Automation Science and Engineering.

[96]  D. Balding A tutorial on statistical methods for population association studies , 2006, Nature Reviews Genetics.

[97]  É. Tannier,et al.  The Inference of Gene Trees with Species Trees , 2013, Systematic biology.

[98]  D. Tollervey,et al.  Mapping the Human miRNA Interactome by CLASH Reveals Frequent Noncanonical Binding , 2013, Cell.

[99]  Jindřich Fanfrlík,et al.  Semiempirical Quantum Chemical PM6 Method Augmented by Dispersion and H-Bonding Correction Terms Reliably Describes Various Types of Noncovalent Complexes. , 2009, Journal of chemical theory and computation.

[100]  Carl Kingsford,et al.  Analysis of the structural variability of topologically associated domains as revealed by Hi-C , 2018, bioRxiv.

[101]  J. Dearden,et al.  QSAR modeling: where have you been? Where are you going to? , 2014, Journal of medicinal chemistry.

[102]  Alper Yilmaz,et al.  A New Network-Based Tool to Analyse Competing Endogenous RNAs , 2020, ISBRA.

[103]  Luca Maria Gambardella,et al.  Mitosis Detection in Breast Cancer Histology Images with Deep Neural Networks , 2013, MICCAI.

[104]  Wooyoung Kim,et al.  Prediction of essential proteins using topological properties in GO-pruned PPI network based on machine learning methods , 2012 .

[105]  W. Bialek,et al.  Stability and Nuclear Dynamics of the Bicoid Morphogen Gradient , 2007, Cell.

[106]  F. Lombardo,et al.  Experimental and computational approaches to estimate solubility and permeability in drug discovery and development settings. , 2001, Advanced drug delivery reviews.

[107]  Yuzhen Ye,et al.  A Parsimony Approach to Biological Pathway Reconstruction/Inference for Genomes and Metagenomes , 2009, PLoS Comput. Biol..

[108]  Hiroyuki Ogata,et al.  KEGG: Kyoto Encyclopedia of Genes and Genomes , 1999, Nucleic Acids Res..

[109]  Jie Ren,et al.  Alignment-free \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{upgreek} \usepackage{mathrsfs} \setlength{\oddsidemargin}{-69pt} \begin{document} }{}$d_2^*$\end{document} oligonucleotide frequency dissi , 2016, Nucleic acids research.

[110]  Frank Neese,et al.  Software update: the ORCA program system, version 4.0 , 2018 .

[111]  D. Sankoff Minimal Mutation Trees of Sequences , 1975 .

[112]  Garrison W. Cottrell,et al.  Understanding Convolution for Semantic Segmentation , 2017, 2018 IEEE Winter Conference on Applications of Computer Vision (WACV).

[113]  Daniel Sánchez Morillo,et al.  Probabilistic neural network approach for the detection of SAHS from overnight pulse oximetry , 2012, Medical & Biological Engineering & Computing.

[114]  H. Meinhardt,et al.  A theory of biological pattern formation , 1972, Kybernetik.

[115]  Dimitrios Kleftogiannis,et al.  Identification of single nucleotide variants using position-specific error estimation in deep sequencing data , 2018 .

[116]  Thomas Steiner,et al.  C–H···O hydrogen bonding in crystals , 1996 .

[117]  Xin Fan,et al.  Neighborhood Constraint Matrix Completion for Drug-Target Interaction Prediction , 2018, PAKDD.

[118]  Saurabh Sinha,et al.  A statistical method for alignment-free comparison of regulatory sequences , 2007, ISMB/ECCB.

[119]  Yong Zi Tan,et al.  Reducing effects of particle adsorption to the air-water interface in cryoEM , 2018, Nature Methods.

[120]  Peng Du,et al.  Species Tree and Reconciliation Estimation under a Duplication-Loss-Coalescence Model , 2018, BCB.

[121]  Gyanesh Sharma,et al.  Synthetase Tyrosyl-tRNA stearothermophilus Bacillus Catalytic Mechanism of Temperature-dependent Change in the Thermodynamic Analysis Reveals a Enzyme Catalysis and Regulation : , 2009 .

[122]  Roberto Hornero,et al.  Utility of AdaBoost to Detect Sleep Apnea-Hypopnea Syndrome From Single-Channel Airflow , 2016, IEEE Transactions on Biomedical Engineering.

[123]  Cinzia Pizzi,et al.  Higher recall in metagenomic sequence classification exploiting overlapping reads , 2016, BMC Genomics.

[124]  Elena Marchiori,et al.  Gaussian interaction profile kernels for predicting drug-target interaction , 2011, Bioinform..

[125]  Vincent Ranwez,et al.  Inferring incomplete lineage sorting, duplications, transfers and losses with reconciliations. , 2017, Journal of theoretical biology.

[126]  Vladimir Poroikov,et al.  QSAR Modelling of Rat Acute Toxicity on the Basis of PASS Prediction , 2011, Molecular informatics.

[127]  L. Bachmann,et al.  Reconstructing mitochondrial genomes directly from genomic next-generation sequencing reads—a baiting and iterative mapping approach , 2013, Nucleic acids research.

[128]  Yi Pan,et al.  DNRLMF-MDA:Predicting microRNA-Disease Associations Based on Similarities of microRNAs and Diseases , 2019, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[129]  David S. Wishart,et al.  DrugBank: a knowledgebase for drugs, drug actions and drug targets , 2007, Nucleic Acids Res..

[130]  J. Shendure,et al.  A general framework for estimating the relative pathogenicity of human genetic variants , 2014, Nature Genetics.

[131]  Ronald W. Davis,et al.  Functional characterization of the S. cerevisiae genome by gene deletion and parallel analysis. , 1999, Science.

[132]  Yunfan Fan,et al.  Nanopore sequencing detects structural variants in cancer , 2015, bioRxiv.

[133]  Andrew R. Webster,et al.  Complex structural variants in Mendelian disorders: identification and breakpoint resolution using short- and long-read genome sequencing , 2018, Genome Medicine.

[134]  I. Măndoiu,et al.  Towards accurate detection and genotyping of expressed variants from whole transcriptome sequencing data , 2011, BMC Genomics.

[135]  Jianxin Wang,et al.  Prediction of Microbe-Drug Associations Based on KATZ Measure , 2019, 2019 IEEE International Conference on Bioinformatics and Biomedicine (BIBM).

[136]  David Kosman,et al.  Analysis of pattern precision shows that Drosophila segmentation develops substantial independence from gradients of maternal gene products , 2006, Developmental dynamics : an official publication of the American Association of Anatomists.

[137]  Wooyoung Kim,et al.  NemoProfile : Effective representation for network motif and their instances , 2016 .

[138]  Alfred V. Aho,et al.  Inferring a Tree from Lowest Common Ancestors with an Application to the Optimization of Relational Expressions , 1981, SIAM J. Comput..

[139]  Matthew P. Repasky,et al.  Extra precision glide: docking and scoring incorporating a model of hydrophobic enclosure for protein-ligand complexes. , 2006, Journal of medicinal chemistry.

[140]  Junzhou Huang,et al.  Imaging Biomarker Discovery for Lung Cancer Survival Prediction , 2016, MICCAI.

[141]  Jürgen Schmidhuber,et al.  Deep learning in neural networks: An overview , 2014, Neural Networks.

[142]  Jennifer Lu,et al.  Improved metagenomic analysis with Kraken 2 , 2019, Genome Biology.

[143]  Louxin Zhang,et al.  Structural properties of the reconciliation space and their applications in enumerating nearly-optimal reconciliations between a gene tree and a species tree , 2011, BMC Bioinformatics.

[144]  António Amorim,et al.  Mitochondrial DNA in human identification: a review , 2019, PeerJ.

[145]  Michal Linial,et al.  ProFET: Feature engineering captures high-level protein functions , 2015, Bioinform..

[146]  Munehiro Fukuda,et al.  MASS-Based NemoProfile Construction for an Efficient Network Motif Search , 2016, 2016 IEEE International Conferences on Big Data and Cloud Computing (BDCloud), Social Computing and Networking (SocialCom), Sustainable Computing and Communications (SustainCom) (BDCloud-SocialCom-SustainCom).

[147]  Grace X. Y. Zheng,et al.  Massively parallel digital transcriptional profiling of single cells , 2016, Nature Communications.

[148]  Andrey V. Kajava,et al.  T-REKS: identification of Tandem REpeats in sequences with a K-meanS based algorithm , 2009, Bioinform..

[149]  John L. Klepeis,et al.  Molecular dynamics - Scalable algorithms for molecular dynamics simulations on commodity clusters , 2006, SC.

[150]  Jonas S. Almeida,et al.  Alignment-free sequence comparison-a review , 2003, Bioinform..

[151]  Bolei Zhou,et al.  Learning Deep Features for Discriminative Localization , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[152]  Ran Libeskind-Hadas,et al.  Multiple Optimal Reconciliations Under the Duplication-Loss-Coalescence Model , 2019, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[153]  Timothy O. Laumann,et al.  Functional Network Organization of the Human Brain , 2011, Neuron.

[154]  R. Page Maps between trees and cladistic analysis of historical associations among genes , 1994 .

[155]  Mireille Régnier,et al.  Short fuzzy tandem repeats in genomic sequences, identification, and possible role in regulation of gene expression , 2006, Bioinform..

[156]  Young Do Kwon,et al.  Structure-Based Design of a Small Molecule CD4-Antagonist with Broad Spectrum Anti-HIV-1 Activity. , 2015, Journal of medicinal chemistry.

[157]  David Wingate,et al.  ProSPr: Democratized Implementation of Alphafold Protein Distance Prediction Network , 2019, bioRxiv.

[158]  Alex T. Kalinka,et al.  The earliest transcribed zygotic genes are short, newly evolved, and different across species. , 2014, Cell reports.

[159]  Hui Zhang,et al.  Applications of Machine Learning Methods in Drug Toxicity Prediction. , 2018, Current topics in medicinal chemistry.

[160]  Matteo Comin,et al.  On the comparison of regulatory sequences with multiple resolution Entropic Profiles , 2016, BMC Bioinformatics.

[161]  Julio O. Ortiz,et al.  Mapping 70S ribosomes in intact cells by cryoelectron tomography and pattern recognition. , 2006, Journal of structural biology.

[162]  Varan Govind,et al.  Glutathione Conformations and Its Implications for in vivo Magnetic Resonance Spectroscopy , 2017, Journal of Alzheimer's disease : JAD.

[163]  R. Durbin,et al.  Mapping Quality Scores Mapping Short Dna Sequencing Reads and Calling Variants Using P

, 2022 .

[164]  Alexandre M J J Bonvin,et al.  Are scoring functions in protein-protein docking ready to predict interactomes? Clues from a novel binding affinity benchmark. , 2010, Journal of proteome research.

[165]  Zhiping Weng,et al.  ZRANK: Reranking protein docking predictions with an optimized energy function , 2007, Proteins.

[166]  Maciej Niedzwiecki,et al.  Automated detection of sleep apnea and hypopnea events based on robust airflow envelope tracking , 2014, 2014 22nd European Signal Processing Conference (EUSIPCO).

[167]  F. Gonzalez,et al.  Human cytochromes P450: evolution and cDNA-directed expression. , 1992, Environmental health perspectives.

[168]  Pavel Skums,et al.  Inference of genetic relatedness between viral quasispecies from sequencing data , 2017, BMC Genomics.

[169]  Dongbo Bu,et al.  DIFFUSE: predicting isoform functions from sequences and expression profiles via deep learning , 2019, Bioinform..

[170]  Ie-Bin Lian,et al.  Summarizing techniques that combine three non-parametric scores to detect disease-associated 2-way SNP-SNP interactions. , 2014, Gene.

[171]  Nikolai A. Kudryashov,et al.  Information decomposition method to analyze symbolical sequences , 2003 .

[172]  Bin Li,et al.  Applications of machine learning in drug discovery and development , 2019, Nature Reviews Drug Discovery.

[173]  Eugene V. Korotkov,et al.  Search for regions with periodicity using the random position weight matrices in the C. elegans genome , 2017, Int. J. Data Min. Bioinform..

[174]  E. Birney,et al.  Patterns of somatic mutation in human cancer genomes , 2007, Nature.

[175]  P. Thomas Fletcher,et al.  Riemannian Regression and Classification Models of Brain Networks Applied to Autism , 2018, CNI@MICCAI.

[176]  Nina Golyandina,et al.  Two-Exponential Models of Gene Expression Patterns for Noisy Experimental Data , 2017, J. Comput. Biol..

[177]  S. Ehrlich,et al.  Essential Bacillus subtilis genes , 2003, Proceedings of the National Academy of Sciences of the United States of America.

[178]  Hongdong Li,et al.  Systematically Differentiating Functions for Alternatively Spliced Isoforms through Integrating RNA-seq Data , 2013, PLoS Comput. Biol..

[179]  Kaiming He,et al.  Faster R-CNN: Towards Real-Time Object Detection with Region Proposal Networks , 2015, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[180]  Jure Leskovec,et al.  Inductive Representation Learning on Large Graphs , 2017, NIPS.

[181]  Wooyoung Kim,et al.  NemoProfile as an efficient approach to network motif analysis with instance collection , 2017, BMC Bioinformatics.

[182]  H. C. Van Der Plas,et al.  The Sn (ANRORC) Mechanism: A new Mechanism for Nucleophilic Substitution , 1978 .

[183]  D. Dey,et al.  Automated detection of apnea and hypopnea events , 2012, 2012 Third International Conference on Emerging Applications of Information Technology.

[184]  K. Kinzler,et al.  Cancer Genome Landscapes , 2013, Science.

[185]  Peng Gao,et al.  Deregulation of microRNA expression occurs early and accumulates in early stages of HBV-associated multistep hepatocarcinogenesis. , 2011, Journal of hepatology.

[186]  Paul Krause,et al.  Feature combination networks for the interpretation of statistical machine learning models: application to Ames mutagenicity , 2014, Journal of Cheminformatics.

[187]  D. Gusfield Integer Linear Programming in Computational and Systems Biology , 2019 .

[188]  Hyunju Lee,et al.  Integration of MicroRNA, mRNA, and Protein Expression Data for the Identification of Cancer-Related MicroRNAs , 2017, PloS one.

[189]  Lior Pachter,et al.  Near-optimal probabilistic RNA-seq quantification , 2016, Nature Biotechnology.

[190]  S E Belanger,et al.  Mode of Action (MOA) Assignment Classifications for Ecotoxicology: An Evaluation of Approaches. , 2017, Environmental science & technology.

[191]  W. O. Kermack,et al.  A contribution to the mathematical theory of epidemics , 1927 .

[192]  Roberto Hornero,et al.  Pattern recognition in airflow recordings to assist in the sleep apnoea–hypopnoea syndrome diagnosis , 2013, Medical & Biological Engineering & Computing.

[193]  Jure Leskovec,et al.  node2vec: Scalable Feature Learning for Networks , 2016, KDD.

[194]  The Uniprot Consortium,et al.  UniProt: a hub for protein information , 2014, Nucleic Acids Res..

[195]  Matthew W. Hahn,et al.  Comparative genomics of centrality and essentiality in three eukaryotic protein-interaction networks. , 2005, Molecular biology and evolution.

[196]  Michael J. Sanderson,et al.  The prevalence of terraced treescapes in analyses of phylogenetic data sets , 2018, BMC Evolutionary Biology.

[197]  Matteo Comin,et al.  Assembly-free genome comparison based on next-generation sequencing reads and variable length patterns , 2014, BMC Bioinformatics.

[198]  Mert R. Sabuncu,et al.  3D Convolutional Neural Networks for Classification of Functional Connectomes , 2018, DLMIA/ML-CDS@MICCAI.

[199]  Matteo Comin,et al.  Indexing k-mers in Linear-space for Quality Value Compression , 2019, BIOINFORMATICS.

[200]  David Ryan Koes,et al.  Pharmit: interactive exploration of chemical space , 2016, Nucleic Acids Res..

[201]  E. Myers,et al.  Basic local alignment search tool. , 1990, Journal of molecular biology.

[202]  G. Benson,et al.  Tandem repeats finder: a program to analyze DNA sequences. , 1999, Nucleic acids research.

[203]  S. Nelson,et al.  BFAST: An Alignment Tool for Large Scale Genome Resequencing , 2009, PloS one.

[204]  Yi Pan,et al.  Essential Protein Discovery Based on Network Motif and Gene Ontology , 2011, 2011 IEEE International Conference on Bioinformatics and Biomedicine.

[205]  Núria López-Bigas,et al.  Differences in the evolutionary history of disease genes affected by dominant or recessive mutations , 2006, BMC Genomics.

[206]  Bengt Sennblad,et al.  Gene tree reconstruction and orthology analysis based on an integrated model for duplications and sequence evolution , 2004, RECOMB.

[207]  Ozlem Keskin,et al.  PRISM: a web server and repository for prediction of protein–protein interactions and modeling their 3D complexes , 2014, Nucleic Acids Res..

[208]  Thomas Brüning,et al.  Exploring the association between genetic variation in the SUMO isopeptidase gene USPL1 and breast cancer through integration of data from the population‐based GENICA study and external genetic databases , 2013, International journal of cancer.

[209]  Monzoorul Haque Mohammed,et al.  Classification of metagenomic sequences: methods and challenges , 2012, Briefings Bioinform..

[210]  G. Arndt,et al.  Genome‐wide screening for gene function using RNAi in mammalian cells , 2005, Immunology and cell biology.

[211]  Yi Pan,et al.  Drug repositioning based on comprehensive similarity measures and Bi-Random walk algorithm , 2016, Bioinform..

[212]  Nathan Linial,et al.  Quantifying gene selection in cancer through protein functional alteration bias , 2019, Nucleic acids research.

[213]  Ahmed Albatineh,et al.  Correcting Jaccard and other similarity indices for chance agreement in cluster analysis , 2011, Adv. Data Anal. Classif..

[214]  Anavaj Sakuntabhai,et al.  A variant in the CD209 promoter is associated with severity of dengue disease , 2005, Nature Genetics.

[215]  Mareike Fischer,et al.  Mathematical Aspects of Phylogenetic Groves , 2011, ArXiv.

[216]  Jeffrey Dean,et al.  Efficient Estimation of Word Representations in Vector Space , 2013, ICLR.

[217]  T. Reich,et al.  A perspective on epistasis: limits of models displaying no main effect. , 2002, American journal of human genetics.

[218]  Yaohang Li,et al.  Drug repositioning based on bounded nuclear norm regularization , 2019, Bioinform..

[219]  Daniel Merkle,et al.  Inferring chemical reaction patterns using rule composition in graph grammars , 2012, ArXiv.

[220]  Yuan Zhou,et al.  Learning Structural Genetic Information via Graph Neural Embedding , 2020, ISBRA.

[221]  S. Abbott,et al.  16S rRNA Gene Sequencing for Bacterial Identification in the Diagnostic Laboratory: Pluses, Perils, and Pitfalls , 2007, Journal of Clinical Microbiology.

[222]  David R. Kelley,et al.  Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks , 2012, Nature Protocols.

[223]  Yi Pan,et al.  Cloud computing for detecting high-order genome-wide epistatic interaction via dynamic clustering , 2014, BMC Bioinformatics.

[224]  L. Mirny,et al.  Iterative Correction of Hi-C Data Reveals Hallmarks of Chromosome Organization , 2012, Nature Methods.

[225]  Jing Zhang,et al.  Identifying driver mutations from sequencing data of heterogeneous tumors in the era of personalized genome sequencing , 2014, Briefings Bioinform..

[226]  V. Scaria,et al.  zflncRNApedia: A Comprehensive Online Resource for Zebrafish Long Non-Coding RNAs , 2015, PloS one.

[227]  Iasonas Kokkinos,et al.  DeepLab: Semantic Image Segmentation with Deep Convolutional Nets, Atrous Convolution, and Fully Connected CRFs , 2016, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[228]  O. Gascuel,et al.  A simple, fast, and accurate algorithm to estimate large phylogenies by maximum likelihood. , 2003, Systematic biology.

[229]  Simon C. Potter,et al.  Association scan of 14,500 nonsynonymous SNPs in four diseases identifies autoimmunity variants , 2007, Nature Genetics.

[230]  Neva C. Durand,et al.  Activity-by-Contact model of enhancer-promoter regulation from thousands of CRISPR perturbations , 2019, Nature Genetics.

[231]  Yang Zhang,et al.  Protein-protein complex structure predictions by multimeric threading and template recombination. , 2011, Structure.

[232]  Peter D. Kwong,et al.  Structure-Based Design, Synthesis and Validation of CD4-Mimetic Small Molecule Inhibitors of HIV-1 Entry: Conversion of a Viral Entry Agonist to an Antagonist , 2014, Accounts of chemical research.

[233]  Niema Moshiri,et al.  FAVITES: simultaneous simulation of transmission networks, phylogenetic trees and sequences , 2019, Bioinform..

[234]  M. Kanehisa,et al.  Development of a chemical structure comparison method for integrated analysis of chemical and genomic information in the metabolic pathways. , 2003, Journal of the American Chemical Society.

[235]  Bong-Hee Lee,et al.  The role of p38 MAP kinase and c-Jun N-terminal protein kinase signaling in the differentiation and apoptosis of immortalized neural stem cells. , 2005, Mutation research.

[236]  J. Tiedje,et al.  Naïve Bayesian Classifier for Rapid Assignment of rRNA Sequences into the New Bacterial Taxonomy , 2007, Applied and Environmental Microbiology.

[237]  A. Franco,et al.  NeuroImage: Clinical , 2022 .

[238]  K. Reinert,et al.  RazerS--fast read mapping with sensitivity control. , 2009, Genome research.

[239]  Sven Rahmann,et al.  SimLoRD: Simulation of Long Read Data , 2016, Bioinform..

[240]  Asya Makhro,et al.  S-Glutathionylation of the Na,K-ATPase Catalytic α Subunit Is a Determinant of the Enzyme Redox Sensitivity* , 2012, The Journal of Biological Chemistry.

[241]  Jean-Michel Claverie,et al.  The human gene damage index as a gene-level approach to prioritizing exome variants , 2015, Proceedings of the National Academy of Sciences.

[242]  Igor Mandric,et al.  Metabolic Analysis of Metatranscriptomic Data from Planktonic Communities , 2017, ISBRA.

[243]  J. Drake,et al.  Mutation rates among RNA viruses. , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[244]  Samuel S. Schoenholz,et al.  Neural Message Passing for Quantum Chemistry , 2017, ICML.

[245]  Yongdong Zhang,et al.  ACE-Net: Biomedical Image Segmentation with Augmented Contracting and Expansive Paths , 2019, MICCAI.

[246]  R. Tibshirani,et al.  On testing the significance of sets of genes , 2006, math/0610667.

[247]  Michal Linial,et al.  ASAP: a machine learning framework for local protein properties , 2015, bioRxiv.

[248]  Vladimir Poroikov,et al.  AntiHIV-Pred: web-resource for in silico prediction of anti-HIV/AIDS activity , 2019, Bioinform..

[249]  M. Zavolan,et al.  Analysis of CDS-located miRNA target sites suggests that they can effectively inhibit translation , 2013, Genome research.

[250]  Surabhi Bhargava,et al.  A Dataset and a Technique for Generalized Nuclear Segmentation for Computational Pathology , 2017, IEEE Transactions on Medical Imaging.

[251]  Geoff Holmes,et al.  Benchmarking Attribute Selection Techniques for Discrete Class Data Mining , 2003, IEEE Trans. Knowl. Data Eng..

[252]  Xing Chen,et al.  PBMDA: A novel and effective path-based computational model for miRNA-disease association prediction , 2017, PLoS Comput. Biol..

[253]  Qiang Chen,et al.  Network In Network , 2013, ICLR.

[254]  Benno Schwikowski,et al.  Discovering regulatory and signalling circuits in molecular interaction networks , 2002, ISMB.

[255]  David C. Jones,et al.  Landscape of somatic mutations in 560 breast cancer whole genome sequences , 2016, Nature.

[256]  E Westhof,et al.  RNA–RNA interaction is required for the formation of specific bicoid mRNA 3′ UTR–STAUFEN ribonucleoprotein particles , 1997, The EMBO journal.

[257]  J. Mullikin,et al.  SSAHA: a fast search method for large DNA databases. , 2001, Genome research.

[258]  Ion I. Mandoiu,et al.  Locality Sensitive Imputation for Single-Cell RNA-Seq Data , 2018, bioRxiv.

[259]  Derrick E. Wood,et al.  Kraken: ultrafast metagenomic sequence classification using exact alignments , 2014, Genome Biology.

[260]  Peter Michaely,et al.  Crystal structure of a 12 ANK repeat stack from human ankyrinR , 2002, The EMBO journal.

[261]  Yong Zi Tan,et al.  Routine single particle CryoEM sample and grid characterization by tomography , 2017, bioRxiv.

[262]  Igor V. Tetko,et al.  Combinatorial QSAR Modeling of Chemical Toxicants Tested against Tetrahymena pyriformis , 2008, J. Chem. Inf. Model..

[263]  Manuel L Gonzalez-Garay,et al.  The road from next-generation sequencing to personalized medicine. , 2014, Personalized medicine.

[264]  Antonio Ventosa,et al.  Halomonas neptunia sp. nov., Halomonas sulfidaeris sp. nov., Halomonas axialensis sp. nov. and Halomonas hydrothermalis sp. nov.: halophilic bacteria isolated from deep-sea hydrothermal-vent environments. , 2004, International journal of systematic and evolutionary microbiology.

[265]  Xiaobo Zhou,et al.  Semi-supervised drug-protein interaction prediction from heterogeneous biological spaces , 2010, BMC Systems Biology.

[266]  Karim Elmaaroufi,et al.  Improved deep learning-based macromolecules structure classification from electron cryo-tomograms , 2017, Machine Vision and Applications.

[267]  D. Robinson,et al.  The protein tyrosine kinase family of the human genome , 2000, Oncogene.

[268]  E. Marcotte,et al.  Prioritizing candidate disease genes by network-based boosting of genome-wide association data. , 2011, Genome research.

[269]  Matteo Comin,et al.  Whole-Genome Phylogeny by Virtue of Unic Subwords , 2012, 2012 23rd International Workshop on Database and Expert Systems Applications.

[270]  J. Tcherkezian,et al.  Current knowledge of the large RhoGAP family of proteins , 2007, Biology of the cell.

[271]  E. Holmes,et al.  A new coronavirus associated with human respiratory disease in China , 2020, Nature.

[272]  Osamu Onodera,et al.  Neuroblastoma amplified sequence gene is associated with a novel short stature syndrome characterised by optic nerve atrophy and Pelger–Huët anomaly , 2010, Journal of Medical Genetics.

[273]  Srinivas Aluru,et al.  A Fast Approximate Algorithm for Mapping Long Reads to Large Reference Databases , 2017, bioRxiv.

[274]  Richard Durbin,et al.  Sequence analysis Fast and accurate short read alignment with Burrows – Wheeler transform , 2009 .

[275]  Matteo Comin,et al.  Fast Entropic Profiler: An Information Theoretic Approach for the Discovery of Patterns in Genomes , 2014, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[276]  J. Janin,et al.  Protein–protein interaction and quaternary structure , 2008, Quarterly Reviews of Biophysics.

[277]  Ion I. Mandoiu,et al.  TreeFix-TP: Phylogenetic Error-Correction for Infectious Disease Transmission Network Inference , 2019, bioRxiv.

[278]  Mark Gerstein,et al.  MetaSV: an accurate and integrative structural-variant caller for next generation sequencing , 2015, Bioinform..

[279]  Nuno A. Fonseca,et al.  Patterns of somatic structural variation in human cancer genomes , 2020, Nature.

[280]  Mehmet Gönen,et al.  Predicting drug-target interactions from chemical and genomic kernels using Bayesian matrix factorization , 2012, Bioinform..

[281]  Andrew G. Leach,et al.  Matched molecular pairs as a guide in the optimization of pharmaceutical properties; a study of aqueous solubility, plasma protein binding and oral exposure. , 2006, Journal of medicinal chemistry.

[282]  Rajshekhar Sunderraman,et al.  Deep Ensemble Models for 16S Ribosomal Gene Classification , 2020, ISBRA.

[283]  Daniel Merkle,et al.  A Software Package for Chemically Inspired Graph Transformation , 2016, ICGT.

[284]  Antonino Fiannaca,et al.  Deep learning models for bacteria taxonomic classification of metagenomic data , 2018, BMC Bioinformatics.

[285]  Ingo Bulla,et al.  Phylogenetically resolving epidemiologic linkage , 2016, Proceedings of the National Academy of Sciences.

[286]  Francisco M. De La Vega,et al.  Sequence and structural variation in a human genome uncovered by short-read, massively parallel ligation sequencing using two-base encoding. , 2009, Genome research.

[287]  Gregory Kucherov,et al.  mreps: efficient and flexible detection of tandem repeats in DNA , 2003, Nucleic Acids Res..

[288]  Alexander F. Auch,et al.  MEGAN analysis of metagenomic data. , 2007, Genome research.

[289]  Jingcheng Du,et al.  Gene2vec: distributed representation of genes based on co-expression , 2018, BMC Genomics.

[290]  Nuno Vasconcelos,et al.  Cascade R-CNN: Delving Into High Quality Object Detection , 2017, 2018 IEEE/CVF Conference on Computer Vision and Pattern Recognition.

[291]  Astrid Gall,et al.  PHYLOSCANNER: Inferring Transmission from Within- and Between-Host Pathogen Genetic Diversity , 2017, bioRxiv.

[292]  Eibe Frank,et al.  Large-scale attribute selection using wrappers , 2009, 2009 IEEE Symposium on Computational Intelligence and Data Mining.

[293]  Wolf-Dietrich Heyer,et al.  Homologous Recombination and the Formation of Complex Genomic Rearrangements. , 2019, Trends in cell biology.

[294]  Thomas Brox,et al.  U-Net: Convolutional Networks for Biomedical Image Segmentation , 2015, MICCAI.

[295]  Xiujuan Lei,et al.  Detecting overlapping protein complexes in weighted PPI network based on overlay network chain in quotient space , 2019, BMC Bioinformatics.

[296]  Wenjun Chen,et al.  Cell membrane proteins with high N-glycosylation, high expression and multiple interaction partners are preferred by mammalian viruses as receptors , 2018, Bioinform..

[297]  Faraz Hach,et al.  mrsFAST: a cache-oblivious algorithm for short-read mapping , 2010, Nature Methods.

[298]  Michael Brudno,et al.  SHRiMP: Accurate Mapping of Short Color-space Reads , 2009, PLoS Comput. Biol..

[299]  Ronald W. Davis,et al.  Functional profiling of the Saccharomyces cerevisiae genome , 2002, Nature.

[300]  Z. Weng,et al.  ZDOCK: An initial‐stage protein‐docking algorithm , 2003, Proteins.

[301]  Mihaela Zavolan,et al.  Quantifying the strength of miRNA-target interactions. , 2015, Methods.

[302]  Laurens van der Maaten,et al.  Accelerating t-SNE using tree-based algorithms , 2014, J. Mach. Learn. Res..

[303]  Yi Pan,et al.  Predicting MicroRNA-Disease Associations Based on Improved MicroRNA and Disease Similarities , 2018, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[304]  Matteo Comin,et al.  MetaCon: unsupervised clustering of metagenomic contigs with probabilistic k-mers statistics and coverage , 2019, BMC Bioinformatics.

[305]  Chrystopher L. Nehaniv,et al.  Computational Holonomy Decomposition of Transformation Semigroups , 2015 .

[306]  Jian Peng,et al.  Template-based protein structure modeling using the RaptorX web server , 2012, Nature Protocols.

[307]  Alexandros Stamatakis,et al.  Time and memory efficient likelihood-based tree searches on phylogenomic alignments with missing data , 2010, Bioinform..

[308]  L Leoncini,et al.  Inhibition of miR-9 de-represses HuR and DICER1 and impairs Hodgkin lymphoma tumour outgrowth in vivo , 2012, Oncogene.

[309]  Trevor Darrell,et al.  Sequence to Sequence -- Video to Text , 2015, 2015 IEEE International Conference on Computer Vision (ICCV).

[310]  P. Pandolfi,et al.  A coding-independent function of gene and pseudogene mRNAs regulates tumour biology , 2010, Nature.

[311]  Fedor V. Fomin,et al.  Exact exponential algorithms , 2013, CACM.

[312]  Jianglin Fan,et al.  Epidermal Growth Factor Receptor-PI3K Signaling Controls Cofilin Activity To Facilitate Herpes Simplex Virus 1 Entry into Neuronal Cells , 2014, mBio.

[313]  David Posada,et al.  SimPhy: Phylogenomic Simulation of Gene, Locus, and Species Trees , 2015, bioRxiv.

[314]  Tongxing Lu,et al.  Solution of the matrix equation AX−XB=C , 2005, Computing.

[315]  Heng Li,et al.  Minimap2: fast pairwise alignment for long nucleotide sequences , 2017 .

[316]  Michael C. Schatz,et al.  Oxford Nanopore Sequencing, Hybrid Error Correction, and de novo Assembly of a Eukaryotic Genome , 2015 .

[317]  Chrystopher L. Nehaniv,et al.  Hierarchical Coordinate Systems for Understanding Complexity and its Evolution, with Applications to Genetic Regulatory Networks , 2008, Artificial Life.

[318]  F. Crick Diffusion in Embryogenesis , 1970, Nature.

[319]  Evan W. Newell,et al.  High-Dimensional Analysis Delineates Myeloid and Lymphoid Compartment Remodeling during Successful Immune-Checkpoint Cancer Therapy , 2018, Cell.

[320]  Alessio Vecchio,et al.  TRStalker: an efficient heuristic for finding fuzzy tandem repeats , 2010, Bioinform..

[321]  E V Korotkov,et al.  Classification analysis of triplet periodicity in protein-coding regions of genes. , 2008, Gene.

[322]  Sheng-Ping L. Hwang,et al.  Integration of CNS survival and differentiation by HIF2α , 2011, Cell Death and Differentiation.

[323]  Rohita Sinha,et al.  Docking by structural similarity at protein‐protein interfaces , 2010, Proteins.

[324]  Wooyoung Kim,et al.  Network Motif Detection: Algorithms, Parallel and Cloud Computing,and Related Tools , 2013 .

[325]  Barbara Telfer,et al.  A10 Using the molecular epidemiology of HIV transmission in New South Wales to inform public health response: Assessing the representativeness of linked phylogenetic data , 2018, Virus Evolution.

[326]  Hongyu Guo,et al.  Diagnosis of ASD from rs-fMRI Images Based on Brain Dynamic Networks , 2020, ISBRA.

[327]  Torsten Schwede,et al.  Critical assessment of methods of protein structure prediction (CASP)—Round XIII , 2019, Proteins.

[328]  Jacob D. Durrant,et al.  NNScore 2.0: A Neural-Network Receptor–Ligand Scoring Function , 2011, J. Chem. Inf. Model..

[329]  Cathy H. Wu,et al.  UniProt: the Universal Protein knowledgebase , 2004, Nucleic Acids Res..

[330]  Yi Pan,et al.  Prediction of Essential Proteins Based on Overlapping Essential Modules , 2014, IEEE Transactions on NanoBioscience.

[331]  A. Barabasi,et al.  Lethality and centrality in protein networks , 2001, Nature.

[332]  Vikram Agarwal,et al.  Impact of MicroRNA Levels, Target-Site Complementarity, and Cooperativity on Competing Endogenous RNA-Regulated Gene Expression , 2016, Molecular cell.

[333]  Oliver Eulenstein,et al.  Groves of Phylogenetic Trees , 2009 .

[334]  Céline Scornavacca Supertree methods for phylogenomics , 2009 .

[335]  Michael C. Schatz,et al.  Accurate detection of complex structural variations using single molecule sequencing , 2017, Nature Methods.

[336]  A. Tee,et al.  The role of mTOR signalling in neurogenesis, insights from tuberous sclerosis complex. , 2016, Seminars in cell & developmental biology.

[337]  K. Kinzler,et al.  Evaluating the evaluation of cancer driver genes , 2016, Proceedings of the National Academy of Sciences.

[338]  Barnaby Martin,et al.  The complexity of surjective homomorphism problems - a survey , 2011, Discret. Appl. Math..

[339]  Sakib Mostafa,et al.  Diagnosis of Autism Spectrum Disorder Based on Eigenvalues of Brain Networks , 2019, IEEE Access.

[340]  S. Tavazoie,et al.  TMEM2 Is a SOX4-Regulated Gene That Mediates Metastatic Migration and Invasion in Breast Cancer. , 2016, Cancer research.

[341]  Jonathan A Eisen,et al.  Environmental Shotgun Sequencing: Its Potential and Challenges for Studying the Hidden World of Microbes , 2007, PLoS biology.

[342]  Gregory Kucherov,et al.  Spaced seeds improve k-mer-based metagenomic classification , 2015, Bioinform..

[343]  Ravi Narasimhan,et al.  Detection of sleep apnea on a per-second basis using respiratory signals , 2013, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).

[344]  Matthew Hall,et al.  Epidemic Reconstruction in a Phylogenetics Framework: Transmission Trees as Partitions of the Node Set , 2014, PLoS Comput. Biol..

[345]  Ruiqiang Li,et al.  SOAP: short oligonucleotide alignment program , 2008, Bioinform..

[346]  Javier De Las Rivas,et al.  Protein–Protein Interactions Essentials: Key Concepts to Building and Analyzing Interactome Networks , 2010, PLoS Comput. Biol..

[347]  John J. Irwin,et al.  ZINC 15 – Ligand Discovery for Everyone , 2015, J. Chem. Inf. Model..

[348]  R. Zecchina,et al.  Integrated transcriptional and competitive endogenous RNA networks are cross-regulated in permissive molecular environments , 2013, Proceedings of the National Academy of Sciences.

[349]  H. Milting,et al.  Supplemental Material , 2004 .

[350]  Robert J Weatheritt,et al.  Autism spectrum disorder: insights into convergent mechanisms from transcriptomics , 2018, Nature Reviews Genetics.

[351]  Zhengwei Zhu,et al.  Templates are available to model nearly all complexes of structurally characterized proteins , 2012, Proceedings of the National Academy of Sciences.

[352]  J. Ross Quinlan,et al.  Induction of Decision Trees , 1986, Machine Learning.

[353]  I. Adzhubei,et al.  Predicting Functional Effect of Human Missense Mutations Using PolyPhen‐2 , 2013, Current protocols in human genetics.

[354]  Falk Schreiber,et al.  MAVisto: a tool for the exploration of network motifs , 2005, Bioinform..

[355]  Dan Wang,et al.  GRSR: a tool for deriving genome rearrangement scenarios from multiple unichromosomal genome sequences , 2018, BMC Bioinformatics.

[356]  Matteo Comin,et al.  Fast Alignment-free Comparison for Regulatory Sequences using Multiple Resolution Entropic Profiles , 2015, BIOINFORMATICS.

[357]  Matteo Comin,et al.  Clustering of reads with alignment-free measures and quality values , 2014, Algorithms for Molecular Biology.

[358]  Mark Achtman,et al.  A Phylogenetic Perspective on Molecular Epidemiology , 2002 .

[359]  Eugene Stepanov,et al.  Structural Transition States Explored With Minimalist Coarse Grained Models: Applications to Calmodulin , 2019, Front. Mol. Biosci..

[360]  Ilya M. Flyamer,et al.  Single-nucleus Hi-C reveals unique chromatin reorganization at oocyte-to-zygote transition , 2017, Nature.

[361]  Mark I. McCarthy,et al.  A brief history of human disease genetics , 2020, Nature.

[362]  Lior Rokach,et al.  Ensemble-based classifiers , 2010, Artificial Intelligence Review.

[363]  Patrick Aloy,et al.  Assessing the applicability of template-based protein docking in the twilight zone. , 2014, Structure.

[364]  Rajshekhar Sunderraman,et al.  Comparative Study Using Neural Networks for 16S Ribosomal Gene Classification , 2020, J. Comput. Biol..

[365]  A. Tanay,et al.  Multiscale 3D Genome Rewiring during Mouse Neural Development , 2017, Cell.

[366]  Alexander Spirov,et al.  Cortical movement of Bicoid in early Drosophila embryos is actin- and microtubule-dependent and disagrees with the SDD diffusion model , 2017, PloS one.

[367]  Leonardo Astudillo,et al.  Monogenic neurological disorders of sphingolipid metabolism. , 2015, Biochimica et biophysica acta.

[368]  Sahar Asadi,et al.  Kavosh: a new algorithm for finding network motifs , 2009, BMC Bioinformatics.

[369]  James J. P. Stewart,et al.  Optimization of parameters for semiempirical methods VI: more modifications to the NDDO approximations and re-optimization of parameters , 2012, Journal of Molecular Modeling.

[370]  Ricardo Villamarín-Salomón,et al.  ClinVar: public archive of interpretations of clinically relevant variants , 2015, Nucleic Acids Res..

[371]  N Howell,et al.  Clinical mitochondrial genetics , 1999, Journal of medical genetics.

[372]  James Bailey,et al.  Alternative Clustering Analysis: A Review , 2018, Data Clustering: Algorithms and Applications.

[373]  W. Pangborn,et al.  Structural basis for androgen specificity and oestrogen synthesis in human aromatase , 2009, Nature.

[374]  Fredrik H. Karlsson,et al.  Symptomatic atherosclerosis is associated with an altered gut metagenome , 2012, Nature Communications.

[375]  Antonino Fiannaca,et al.  Probabilistic topic modeling for the analysis and classification of genomic sequences , 2015, BMC Bioinformatics.

[376]  Tandy Warnow,et al.  Supertree Construction: Opportunities and Challenges , 2018, 1805.03530.

[377]  Electron Kebebew,et al.  Somatic HIF2A gain-of-function mutations in paraganglioma with polycythemia. , 2012, The New England journal of medicine.

[378]  Mukul S. Bansal,et al.  Most parsimonious reconciliation in the presence of gene duplication, loss, and deep coalescence using labeled coalescent trees , 2014, Genome research.

[379]  V. Tumanyan,et al.  Coexistence of different base periodicities in prokaryotic genomes as related to DNA curvature, supercoiling, and transcription. , 2011, Genomics.

[380]  Glenn Tesler,et al.  Mapping single molecule sequencing reads using basic local alignment with successive refinement (BLASR): application and theory , 2012, BMC Bioinformatics.

[381]  Se-Ran Jun,et al.  Alignment-free genome comparison with feature frequency profiles (FFP) and optimal resolutions , 2009, Proceedings of the National Academy of Sciences.

[382]  Dr. Susumu Ohno Evolution by Gene Duplication , 1970, Springer Berlin Heidelberg.

[383]  Chi-Ying F. Huang,et al.  miRTarBase: a database curates experimentally validated microRNA–target interactions , 2010, Nucleic Acids Res..

[384]  Vladimir Poroikov,et al.  ROSC-Pred: web-service for rodent organ-specific carcinogenicity prediction , 2018, Bioinform..

[385]  Zhi Zhang,et al.  Bag of Tricks for Image Classification with Convolutional Neural Networks , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[386]  Manolis Kellis,et al.  Deep learning for regulatory genomics , 2015, Nature Biotechnology.

[387]  Manolis Kellis,et al.  Unified modeling of gene duplication, loss, and coalescence using a locus tree. , 2012, Genome research.

[388]  Steven Weaver,et al.  HIV-TRACE (TRAnsmission Cluster Engine): a Tool for Large Scale Molecular Epidemiology of HIV-1 and Other Rapidly Evolving Pathogens. , 2018, Molecular biology and evolution.

[389]  Kishori M. Konwar,et al.  MetaPathways: a modular pipeline for constructing pathway/genome databases from environmental sequence information , 2013, BMC Bioinformatics.

[390]  P. Woo,et al.  Then and now: use of 16S rDNA gene sequencing for bacterial identification and discovery of novel bacteria in clinical microbiology laboratories. , 2008, Clinical microbiology and infection : the official publication of the European Society of Clinical Microbiology and Infectious Diseases.

[391]  Michael J Silverberg,et al.  Trends in the Molecular Epidemiology and Genetic Mechanisms of Transmitted Human Immunodeficiency Virus Type 1 Drug Resistance in a Large US Clinic Population , 2018, Clinical infectious diseases : an official publication of the Infectious Diseases Society of America.

[392]  Daniel G. MacArthur,et al.  The ExAC browser: displaying reference data information from over 60 000 exomes , 2016, bioRxiv.

[393]  Zhiqiang Hu,et al.  Signet Ring Cell Detection with a Semi-supervised Learning Framework , 2019, IPMI.

[394]  K. Tomczak,et al.  The Cancer Genome Atlas (TCGA): an immeasurable source of knowledge , 2015, Contemporary oncology.

[395]  Howard Y. Chang,et al.  Transposition of native chromatin for fast and sensitive epigenomic profiling of open chromatin, DNA-binding proteins and nucleosome position , 2013, Nature Methods.

[396]  Mohammed El-Kebir,et al.  SharpTNI: Counting and Sampling Parsimonious Transmission Networks under a Weak Bottleneck , 2019, bioRxiv.

[397]  Rajeev K. Varshney,et al.  Structural variations in plant genomes , 2014, Briefings in functional genomics.

[398]  Phillip A Sharp,et al.  Endogenous miRNA and target concentrations determine susceptibility to potential ceRNA competition. , 2014, Molecular cell.

[399]  Gaël Varoquaux,et al.  Scikit-learn: Machine Learning in Python , 2011, J. Mach. Learn. Res..

[400]  B. Roe,et al.  A core gut microbiome in obese and lean twins , 2008, Nature.

[401]  Qiang Feng,et al.  A metagenome-wide association study of gut microbiota in type 2 diabetes , 2012, Nature.

[402]  Matteo Comin,et al.  SKraken: Fast and Sensitive Classification of Short Metagenomic Reads based on Filtering Uninformative k-mers , 2017, BIOINFORMATICS.

[403]  B. Baum Combining trees as a way of combining data sets for phylogenetic inference, and the desirability of combining gene trees , 1992 .

[404]  Hao Luo,et al.  Accurate prediction of human essential genes using only nucleotide composition and association information , 2016, bioRxiv.

[405]  W. Ansorge Next-generation DNA sequencing techniques. , 2009, New biotechnology.

[406]  Mong-Li Lee,et al.  NeMoFinder: dissecting genome-wide protein-protein interactions with meso-scale network motifs , 2006, KDD '06.

[407]  Russell L. Malmberg,et al.  A standardized kinesin nomenclature , 2004, The Journal of cell biology.

[408]  Jianxin Wang,et al.  IILLS: predicting virus-receptor interactions based on similarity and semi-supervised learning , 2019, BMC Bioinformatics.

[409]  Hedi Peterson,et al.  g:Profiler—a web-based toolset for functional profiling of gene lists from large-scale experiments , 2007, Nucleic Acids Res..

[410]  Frank Alber,et al.  High-throughput subtomogram alignment and classification by Fourier space constrained fast volumetric matching. , 2012, Journal of structural biology.

[411]  Daniel Merkle,et al.  Atom Tracking Using Cayley Graphs , 2020, ISBRA.

[412]  Tao Liu,et al.  TreeFam: a curated database of phylogenetic trees of animal gene families , 2005, Nucleic Acids Res..

[413]  Ilya A Vakser,et al.  Protein-protein docking: from interaction to interactome. , 2014, Biophysical journal.

[414]  J. Lupski,et al.  Mechanisms underlying structural variant formation in genomic disorders , 2016, Nature Reviews Genetics.

[415]  Nima Tajbakhsh,et al.  UNet++: A Nested U-Net Architecture for Medical Image Segmentation , 2018, DLMIA/ML-CDS@MICCAI.

[416]  Maya Gokhale,et al.  Scalable metagenomic taxonomy classification using a reference genome database , 2013, Bioinform..

[417]  H. Berman The Protein Data Bank: a historical perspective. , 2008, Acta crystallographica. Section A, Foundations of crystallography.

[418]  Trevor Darrell,et al.  Fully Convolutional Networks for Semantic Segmentation , 2017, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[419]  Atul J. Butte,et al.  Ten Years of Pathway Analysis: Current Approaches and Outstanding Challenges , 2012, PLoS Comput. Biol..

[420]  Eugene N Muratov,et al.  Universal Approach for Structural Interpretation of QSAR/QSPR Models , 2013, Molecular informatics.

[421]  Jure Leskovec,et al.  Hierarchical Graph Representation Learning with Differentiable Pooling , 2018, NeurIPS.

[422]  Leyun Pan,et al.  Multi-Path Dilated Residual Network for Nuclei Segmentation and Detection , 2019, Cells.

[423]  Q. Zou,et al.  Gene2vec: gene subsequence embedding for prediction of mammalian N6-methyladenosine sites from mRNA , 2018, RNA.

[424]  S. Lonardi,et al.  CLARK: fast and accurate classification of metagenomic and genomic sequences using discriminative k-mers , 2015, BMC Genomics.

[425]  Dong Wang,et al.  Inferring the human microRNA functional similarity and functional network based on microRNA-associated diseases , 2010, Bioinform..

[426]  Vladlen Koltun,et al.  Multi-Scale Context Aggregation by Dilated Convolutions , 2015, ICLR.

[427]  F. Khuri,et al.  Targeting protein-protein interactions as an anticancer strategy. , 2013, Trends in pharmacological sciences.

[428]  J. S. Cramer The Origins of Logistic Regression , 2002 .

[429]  Bonnie Berger,et al.  Quality score compression improves genotyping accuracy , 2015, Nature Biotechnology.

[430]  Yoshua Bengio,et al.  Understanding the difficulty of training deep feedforward neural networks , 2010, AISTATS.

[431]  A. Barabasi,et al.  Network medicine : a network-based approach to human disease , 2010 .

[432]  Davide Heller,et al.  STRING v10: protein–protein interaction networks, integrated over the tree of life , 2014, Nucleic Acids Res..

[433]  Yuan Zhou,et al.  Off-Policy Evaluation and Learning from Logged Bandit Feedback: Error Reduction via Surrogate Policy , 2019, ICLR.

[434]  Nasir M. Rajpoot,et al.  Locality Sensitive Deep Learning for Detection and Classification of Nuclei in Routine Colon Cancer Histology Images , 2016, IEEE Trans. Medical Imaging.

[435]  Mike A. Steel,et al.  Characterizing phylogenetically decisive taxon coverage , 2010, Appl. Math. Lett..

[436]  Vikram Agarwal,et al.  Assessing the ceRNA hypothesis with quantitative measurements of miRNA and target abundance. , 2014, Molecular cell.

[437]  Javier Quilez,et al.  Transcription factors orchestrate dynamic interplay between genome topology and gene regulation during cell reprogramming , 2017, Nature Genetics.

[438]  W. Miller,et al.  Aromatase inhibitors and breast cancer. , 1997, Minerva endocrinologica.

[439]  Giorgio Valle,et al.  PASS: a program to align short sequences , 2009, Bioinform..

[440]  Paz Polak,et al.  Cell-of-origin chromatin organization shapes the mutational landscape of cancer , 2015, Nature.

[441]  Nicha C. Dvornek,et al.  Identifying Autism from Resting-State fMRI Using Long Short-Term Memory Networks , 2017, MLMI@MICCAI.

[442]  Chunyan Miao,et al.  Neighborhood Regularized Logistic Matrix Factorization for Drug-Target Interaction Prediction , 2016, PLoS Comput. Biol..

[443]  Junmei Wang,et al.  Development and testing of a general amber force field , 2004, J. Comput. Chem..

[444]  Ron Kohavi,et al.  The Case against Accuracy Estimation for Comparing Induction Algorithms , 1998, ICML.

[445]  M S Waterman,et al.  Identification of common molecular subsequences. , 1981, Journal of molecular biology.

[446]  H. Grosshans,et al.  MicroRNA turnover: when, how, and why. , 2012, Trends in biochemical sciences.

[447]  Matteo Comin,et al.  Better quality score compression through sequence-based quality smoothing , 2019, BMC Bioinformatics.

[448]  Demis Hassabis,et al.  Improved protein structure prediction using potentials from deep learning , 2020, Nature.

[449]  H Peter Soyer,et al.  Detection of HPV E7 Transcription at Single-Cell Resolution in Epidermis. , 2018, The Journal of investigative dermatology.

[450]  Chrystopher L. Nehaniv,et al.  Symmetry structure in discrete models of biochemical systems: natural subsystems and the weak control hierarchy in a new model of computation driven by interactions , 2015, Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences.

[451]  Jun Fu,et al.  Dual Attention Network for Scene Segmentation , 2018, 2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR).

[452]  Geoffrey E. Hinton,et al.  Visualizing Data using t-SNE , 2008 .

[453]  Mark R. Wilson,et al.  Forensics and mitochondrial DNA: applications, debates, and foundations. , 2003, Annual review of genomics and human genetics (Print).

[454]  Feng-Biao Guo,et al.  Applications of four machine learning algorithms in identifying bacterial essential genes based on composition features , 2015, 2015 IEEE China Summit and International Conference on Signal and Information Processing (ChinaSIP).

[455]  Wei Liu,et al.  SSD: Single Shot MultiBox Detector , 2015, ECCV.

[456]  Paul P. Gardner,et al.  An evaluation of the accuracy and speed of metagenome analysis tools , 2015, Scientific Reports.

[457]  Yoshihiro Yamanishi,et al.  Prediction of drug–target interaction networks from the integration of chemical and genomic spaces , 2008, ISMB.

[458]  Paul Bertone,et al.  Systematic comparison of microarray profiling, real-time PCR, and next-generation sequencing technologies for measuring differential microRNA expression. , 2010, RNA.

[459]  D. Bartel MicroRNAs: Target Recognition and Regulatory Functions , 2009, Cell.

[460]  Tomoshige Kino,et al.  Single-Nucleotide Variations of the Human Nuclear Hormone Receptor Genes in 60,000 Individuals , 2017, Journal of the Endocrine Society.

[461]  F. Schreiber,et al.  MODA: an efficient algorithm for network motif discovery in biological networks. , 2009, Genes & genetic systems.

[462]  Guoxian Yu,et al.  HiSeeker: Detecting High-Order SNP Interactions Based on Pairwise SNP Combinations , 2017, Genes.

[463]  Thomas Peterson,et al.  Benchmarking transposable element annotation methods for creation of a streamlined, comprehensive pipeline , 2019, Genome Biology.

[464]  Dan Geiger,et al.  Finding approximate tandem repeats in genomic sequences , 2004, RECOMB.

[465]  Marcel H. Schulz,et al.  Large-scale inference of competing endogenous RNA networks with sparse partial correlation , 2019, Bioinform..

[466]  Daniel Merkle,et al.  Graph Transformations, Semigroups, and Isotopic Labeling , 2019, ISBRA.

[467]  Ron Y. Pinter,et al.  Pathway-Based Functional Analysis of Metagenomes , 2010, RECOMB.

[468]  Ibtissem Grissa,et al.  CRISPRFinder: a web tool to identify clustered regularly interspaced short palindromic repeats , 2007, Nucleic Acids Res..

[469]  David C. Van Essen,et al.  The future of the human connectome , 2012, NeuroImage.

[470]  Lukas Wagner,et al.  A Greedy Algorithm for Aligning DNA Sequences , 2000, J. Comput. Biol..

[471]  Eric F. Wieschaus,et al.  The Formation of the Bicoid Morphogen Gradient Requires Protein Movement from Anteriorly Localized mRNA , 2011, PLoS biology.

[472]  Nicola De Maio,et al.  SCOTTI: Efficient Reconstruction of Transmission within Outbreaks with the Structured Coalescent , 2016, PLoS Comput. Biol..

[473]  J. Sodroski,et al.  Structure of an HIV gp120 envelope glycoprotein in complex with the CD4 receptor and a neutralizing human antibody , 1998, Nature.

[474]  Stefan Schoenfelder,et al.  Hi-C as a tool for precise detection and characterisation of chromosomal rearrangements and copy number variation in human tumours , 2017, Genome Biology.

[475]  Xavier Didelot,et al.  Genomic Infectious Disease Epidemiology in Partially Sampled and Ongoing Outbreaks , 2016, bioRxiv.

[476]  D. Dinges,et al.  Behavioral and physiological consequences of sleep restriction. , 2007, Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine.

[477]  Xiaoming Yuan,et al.  Matrix completion via an alternating direction method , 2012 .

[478]  J. Devillers,et al.  Prediction of acute mammalian toxicity from QSARs and interspecies correlations , 2009, SAR and QSAR in environmental research.

[479]  Jonathan Sebat,et al.  SV2: Accurate Structural Variation Genotyping and De Novo Mutation Detection from Whole Genomes , 2017, bioRxiv.

[480]  O. V. Tin’kov,et al.  QSAR Investigation of Acute Toxicity of Organic Acids and their Derivatives Upon Intraperitoneal Injection in Mice , 2015, Pharmaceutical Chemistry Journal.

[481]  Shiuan Chen,et al.  Aromatase Inhibitors , 2006, Annals of the New York Academy of Sciences.

[482]  Geoffrey E. Hinton,et al.  ImageNet classification with deep convolutional neural networks , 2012, Commun. ACM.

[483]  Kai Zhao,et al.  A pneumonia outbreak associated with a new coronavirus of probable bat origin , 2020, Nature.

[484]  J. Deisenhofer,et al.  The leucine-rich repeat: a versatile binding motif. , 1994, Trends in biochemical sciences.

[485]  Robert Clarke,et al.  Network motif-based identification of breast cancer susceptibility genes , 2008, 2008 30th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[486]  Martin Vingron,et al.  SVIM: structural variant identification using mapped long reads , 2018, bioRxiv.

[487]  J. G. Burleigh,et al.  Synthesis of phylogeny and taxonomy into a comprehensive tree of life , 2014, Proceedings of the National Academy of Sciences.

[488]  Adel Al-Jumaily,et al.  Automated detecting sleep apnea syndrome: A novel system based on genetic SVM , 2011, 2011 11th International Conference on Hybrid Intelligent Systems (HIS).

[489]  Karl J. Friston,et al.  Analysing connectivity with Granger causality and dynamic causal modelling , 2013, Current Opinion in Neurobiology.

[490]  Chiranjib Bhattacharyya,et al.  Incorporating Syntactic and Semantic Information in Word Embeddings using Graph Convolutional Networks , 2018, ACL.

[491]  P. Pandolfi,et al.  A ceRNA Hypothesis: The Rosetta Stone of a Hidden RNA Language? , 2011, Cell.

[492]  Xun Zhu,et al.  Using single nucleotide variations in single-cell RNA-seq to identify subpopulations and genotype-phenotype linkage , 2016, Nature Communications.

[493]  Mehmet Koyutürk,et al.  MOBAS: identification of disease-associated protein subnetworks using modularity-based scoring , 2015, EURASIP J. Bioinform. Syst. Biol..

[494]  E. Mardis,et al.  An obesity-associated gut microbiome with increased capacity for energy harvest , 2006, Nature.

[495]  Jia He,et al.  Discrimination of excess toxicity from narcotic effect: comparison of toxicity of class-based organic chemicals to Daphnia magna and Tetrahymena pyriformis. , 2013, Chemosphere.

[496]  Arun Siddharth Konagurthu,et al.  On the origin of distribution patterns of motifs in biological networks , 2008, BMC Systems Biology.

[497]  Ah Chung Tsoi,et al.  The Graph Neural Network Model , 2009, IEEE Transactions on Neural Networks.

[498]  Eric F. Wieschaus,et al.  Zygotic Genome Activation Triggers the DNA Replication Checkpoint at the Midblastula Transition , 2015, Cell.

[499]  Eric Granger,et al.  Multiple instance learning: A survey of problem characteristics and applications , 2016, Pattern Recognit..

[500]  J. Garcia-Vallejo,et al.  DC-SIGN: The Strange Case of Dr. Jekyll and Mr. Hyde. , 2015, Immunity.

[501]  Ilya A Vakser,et al.  Low-resolution structural modeling of protein interactome. , 2013, Current opinion in structural biology.

[502]  O. V. Tin’kov,et al.  Analysis and Prediction of the Reproductive Toxicity of Organic Compounds of Different Classes using 2D Simplex Representations of Molecular Structure , 2013, Pharmaceutical Chemistry Journal.

[503]  S. Drăghici,et al.  Analysis and correction of crosstalk effects in pathway analysis , 2013, Genome research.

[504]  W. J. Kent,et al.  BLAT--the BLAST-like alignment tool. , 2002, Genome research.

[505]  Hao Ding,et al.  Collaborative matrix factorization with multiple similarities for predicting drug-target interactions , 2013, KDD.

[506]  C. Nüsslein-Volhard,et al.  Multiple steps in the localization of bicoid RNA to the anterior pole of the Drosophila oocyte. , 1989, Development.

[507]  Wei Dai,et al.  Identifying Human Essential Genes by Network Embedding Protein-Protein Interaction Network , 2019, ISBRA.

[508]  Ilya M. Flyamer,et al.  Active chromatin and transcription play a key role in chromosome partitioning into topologically associating domains , 2016, Genome research.

[509]  Takemi Matsui,et al.  Non-contact diagnostic system for sleep apnea–hypopnea syndrome based on amplitude and phase analysis of thoracic and abdominal Doppler radars , 2015, Medical & Biological Engineering & Computing.

[510]  Sakib Mostafa,et al.  A network clustering based feature selection strategy for classifying autism spectrum disorder , 2019, BMC Medical Genomics.

[511]  Thomas Sander,et al.  DataWarrior: An Open-Source Program For Chemistry Aware Data Visualization And Analysis , 2015, J. Chem. Inf. Model..

[512]  J. Holland,et al.  Rapid evolution of RNA viruses. , 1987, Annual review of microbiology.

[513]  Kilian Q. Weinberger,et al.  Densely Connected Convolutional Networks , 2016, 2017 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[514]  Guoxian Yu,et al.  DualWMDR: Detecting epistatic interaction with dual screening and multifactor dimensionality reduction , 2019, Human mutation.

[515]  Aviv Regev,et al.  Purine synthesis promotes maintenance of brain tumor initiating cells in glioma , 2017, Nature Neuroscience.

[516]  Sandro Morganella,et al.  Noncanonical secondary structures arising from non-B DNA motifs are determinants of mutagenesis. , 2018, Genome research.

[517]  Ahmet Akbaş,et al.  Sleep apnea classification based on respiration signals by using ensemble methods. , 2015, Bio-medical materials and engineering.

[518]  K. To,et al.  How the SARS coronavirus causes disease: host or organism? , 2005, The Journal of pathology.

[519]  C. Bannwarth,et al.  B97-3c: A revised low-cost variant of the B97-D density functional method. , 2018, The Journal of chemical physics.

[520]  R. Prayson,et al.  Mutational Heterogeneity in Human Cancers : Origin and Consequences , 2010 .

[521]  Martin Vingron,et al.  Estimation of pairwise sequence similarity of mammalian enhancers with word neighbourhood counts , 2012, Bioinform..

[522]  Bin Ma,et al.  PatternHunter: faster and more sensitive homology search , 2002, Bioinform..

[523]  D. Goldstein,et al.  Genic Intolerance to Functional Variation and the Interpretation of Personal Genomes , 2013, PLoS genetics.

[524]  Bin Ma,et al.  From Gene Trees to Species Trees , 2000, SIAM J. Comput..

[525]  Manuel Holtgrewe,et al.  Mason – A Read Simulator for Second Generation Sequencing Data , 2010 .

[526]  Marmar Moussa,et al.  Computational cell cycle analysis of single cell RNA-Seq data , 2018, bioRxiv.

[527]  Anna Bogdanova,et al.  Cysteine residues 244 and 458–459 within the catalytic subunit of Na,K-ATPase control the enzyme's hydrolytic and signaling function under hypoxic conditions , 2017, Redox biology.

[528]  Leon Di Stefano,et al.  Comprehensive evaluation and characterisation of short read general-purpose structural variant calling software , 2019, Nature Communications.

[529]  Sergey Koren,et al.  Accurate circular consensus long-read sequencing improves variant detection and assembly of a human genome , 2019, Nature Biotechnology.

[530]  B. Cong,et al.  Current developments in forensic interpretation of mixed DNA samples (Review) , 2014, Biomedical reports.

[531]  Cristina Mitrea,et al.  Methods and approaches in the topology-based analysis of biological pathways , 2013, Front. Physiol..

[532]  Brian D. Ondov,et al.  Mash: fast genome and metagenome distance estimation using MinHash , 2015, Genome Biology.

[533]  Mark Wilkinson,et al.  Coping with Abundant Missing Entries in Phylogenetic Inference Using Parsimony , 1995 .

[534]  Simon Mitternacht,et al.  FreeSASA: An open source C library for solvent accessible surface area calculations , 2016, F1000Research.

[535]  Kara L Hamilton-Nelson,et al.  Evidence of novel fine-scale structural variation at autism spectrum disorder candidate loci , 2012, Molecular Autism.

[536]  Núria Queralt-Rosinach,et al.  DisGeNET: a discovery platform for the dynamical exploration of human diseases and their genes , 2015, Database J. Biol. Databases Curation.

[537]  Ulrik Brandes,et al.  On Finding Graph Clusterings with Maximum Modularity , 2007, WG.

[538]  Dimitris Samaras,et al.  Deriving reproducible biomarkers from multi-site resting-state data: An Autism-based example , 2016, NeuroImage.

[539]  Xing Chen,et al.  Adaptive boosting-based computational model for predicting potential miRNA-disease associations , 2019, Bioinform..

[540]  Igor Mandric,et al.  QUENTIN: reconstruction of disease transmissions from viral quasispecies genomic data , 2018, Bioinform..

[541]  Paul Horton,et al.  Parameters for accurate genome alignment , 2010, BMC Bioinformatics.

[542]  Arpita Ghosh,et al.  Metagenomic Analysis and its Applications , 2019, Encyclopedia of Bioinformatics and Computational Biology.

[543]  Max Welling,et al.  Semi-Supervised Classification with Graph Convolutional Networks , 2016, ICLR.

[544]  S. Salzberg,et al.  Centrifuge: rapid and sensitive classification of metagenomic sequences , 2016, bioRxiv.

[545]  Zhiping Weng,et al.  Accelerating Protein Docking in ZDOCK Using an Advanced 3D Convolution Library , 2011, PloS one.

[546]  Alexandros Stamatakis,et al.  RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies , 2014, Bioinform..

[547]  G. Schwarz Estimating the Dimension of a Model , 1978 .

[548]  Renmin Han,et al.  AuTom: A novel automatic platform for electron tomography reconstruction. , 2017, Journal of structural biology.

[549]  Yan Lin,et al.  DEG 5.0, a database of essential genes in both prokaryotes and eukaryotes , 2008, Nucleic Acids Res..

[550]  Z. Deng,et al.  Structural interaction fingerprint (SIFt): a novel method for analyzing three-dimensional protein-ligand binding interactions. , 2004, Journal of medicinal chemistry.

[551]  G Sapiro,et al.  Classification and 3D averaging with missing wedge correction in biological electron tomography. , 2008, Journal of structural biology.

[552]  J. Lupski Structural variation mutagenesis of the human genome: Impact on disease and evolution , 2015, Environmental and molecular mutagenesis.

[553]  S. Lawler,et al.  MicroRNAs in cancer: biomarkers, functions and therapy. , 2014, Trends in molecular medicine.

[554]  Carla C. C. R. de Carvalho,et al.  The Various Roles of Fatty Acids , 2018, Molecules.

[555]  M. Stratton,et al.  A census of amplified and overexpressed human cancer genes , 2010, Nature Reviews Cancer.

[556]  M. Sternberg,et al.  Modelling protein docking using shape complementarity, electrostatics and biochemical information. , 1997, Journal of molecular biology.

[557]  Icgc,et al.  Pan-cancer analysis of whole genomes , 2017, bioRxiv.

[558]  Saravanaraj N. Ayyampalayam,et al.  Phylotranscriptomic analysis of the origin and early diversification of land plants , 2014, Proceedings of the National Academy of Sciences.

[559]  Emma J. Chory,et al.  A Deep Learning Approach to Antibiotic Discovery , 2020, Cell.

[560]  Ronan N. Rouxel,et al.  Differential Use of the C‐Type Lectins L‐SIGN and DC‐SIGN for Phlebovirus Endocytosis , 2016, Traffic.

[561]  Stephanie Spranger,et al.  Acute Liver Failure Meets SOPH Syndrome: A Case Report on an Intermediate Phenotype , 2017, Pediatrics.

[562]  Nicola De Maio,et al.  Bayesian reconstruction of transmission within outbreaks using genomic variants , 2017, bioRxiv.

[563]  Md. Shamsuzzoha Bayzid,et al.  Whole-genome analyses resolve early branches in the tree of life of modern birds , 2014, Science.

[564]  Heng Li,et al.  Minimap and miniasm: fast mapping and de novo assembly for noisy long sequences , 2015, Bioinform..

[565]  Martin Zacharias,et al.  Protein–protein docking with a reduced protein model accounting for side‐chain flexibility , 2003, Protein science : a publication of the Protein Society.

[566]  M. Greicius Resting-state functional connectivity in neuropsychiatric disorders , 2008, Current opinion in neurology.

[567]  Eric Smith,et al.  The Origin and Nature of Life on Earth: The Emergence of the Fourth Geosphere , 2016 .

[568]  Igor V. Tetko,et al.  Online chemical modeling environment (OCHEM): web platform for data storage, model development and publishing of chemical information , 2011, J. Comput. Aided Mol. Des..

[569]  Matteo Comin,et al.  Fast comparison of genomic and meta-genomic reads with alignment-free measures based on quality values , 2016, BMC Medical Genomics.

[570]  A. Gonzalez-Perez,et al.  OncodriveFML: a general framework to identify coding and non-coding regions with cancer driver mutations , 2016, Genome Biology.

[571]  Igor V. Tetko,et al.  Prediction-driven matched molecular pairs to interpret QSARs and aid the molecular optimization process , 2014, Journal of Cheminformatics.

[572]  Emilio Benfenati,et al.  QSAR modeling of Daphnia magna and fish toxicities of biocides using 2D descriptors. , 2019, Chemosphere.

[573]  Ernesto Picardi,et al.  MToolBox: a highly automated pipeline for heteroplasmy annotation and prioritization analysis of human mitochondrial variants in high-throughput sequencing , 2014, Bioinform..

[574]  Sheila Unger,et al.  NBAS mutations cause a multisystem disorder involving bone, connective tissue, liver, immune system, and retina , 2015, American journal of medical genetics. Part A.

[575]  A. Fujimoto,et al.  Cancer whole-genome sequencing: present and future , 2015, Oncogene.

[576]  Pablo Tamayo,et al.  Gene set enrichment analysis: A knowledge-based approach for interpreting genome-wide expression profiles , 2005, Proceedings of the National Academy of Sciences of the United States of America.

[577]  Leland McInnes,et al.  UMAP: Uniform Manifold Approximation and Projection for Dimension Reduction , 2018, ArXiv.

[578]  Uri Alon,et al.  Efficient sampling algorithm for estimating subgraph concentrations and detecting network motifs , 2004, Bioinform..

[579]  Edward C Holmes,et al.  Virological factors that increase the transmissibility of emerging human viruses , 2016, Proceedings of the National Academy of Sciences.

[580]  Niranjan Nagarajan,et al.  Fast and sensitive mapping of nanopore sequencing reads with GraphMap , 2016, Nature Communications.

[581]  W. L. Jorgensen,et al.  Comparison of simple potential functions for simulating liquid water , 1983 .

[582]  James A. Foster,et al.  decisivatoR: an R infrastructure package that addresses the problem of phylogenetic decisiveness , 2013, BCB.

[583]  W Wan,et al.  Cryo-Electron Tomography and Subtomogram Averaging. , 2016, Methods in enzymology.

[584]  Hui Lu,et al.  MULTIPROSPECTOR: An algorithm for the prediction of protein–protein interactions by multimeric threading , 2002, Proteins.

[585]  Sebastian Wernicke,et al.  Efficient Detection of Network Motifs , 2006, IEEE/ACM Transactions on Computational Biology and Bioinformatics.

[586]  Jian Sun,et al.  Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).

[587]  Pavel Polishchuk,et al.  Interpretation of Quantitative Structure-Activity Relationship Models: Past, Present, and Future , 2017, J. Chem. Inf. Model..

[588]  Manu,et al.  Characterization of the Drosophila segment determination morphome. , 2008, Developmental biology.

[589]  Damian Szklarczyk,et al.  STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets , 2018, Nucleic Acids Res..

[590]  W. Baumeister,et al.  Prospects of electron cryotomography to visualize macromolecular complexes inside cellular compartments: implications of crowding. , 2002, Biophysical chemistry.

[591]  Michael R Bardsley,et al.  A functional family-wide screening of SP/KLF proteins identifies a subset of suppressors of KRAS-mediated cell growth. , 2011, The Biochemical journal.

[592]  Igor Mandric,et al.  Fast bootstrapping‐based estimation of confidence intervals of expression levels and differential expression from RNA‐Seq data , 2017, Bioinform..

[593]  Xavier Didelot,et al.  Simultaneous inference of phylogenetic and transmission trees in infectious disease outbreaks , 2017, PLoS Comput. Biol..

[594]  Tianzi Jiang,et al.  Regional homogeneity, functional connectivity and imaging markers of Alzheimer's disease: A review of resting-state fMRI studies , 2008, Neuropsychologia.

[595]  Ian M. Dobbie,et al.  Drosophila patterning is established by differential association of mRNAs with P bodies , 2012, Nature Cell Biology.

[596]  Nezar Abdennur,et al.  Cooler: scalable storage for Hi-C data and other genomically-labeled arrays , 2019, bioRxiv.

[597]  Steven J. M. Jones,et al.  Comprehensive Characterization of Cancer Driver Genes and Mutations , 2018, Cell.

[598]  Bo Wang,et al.  Network enhancement as a general method to denoise weighted biological networks , 2018, Nature Communications.

[599]  Jeffrey Dean,et al.  Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.

[600]  Mikolajczak Algebraic and Structural Automata Theory , 1991 .

[601]  Sebastian Wernicke,et al.  FANMOD: a tool for fast network motif detection , 2006, Bioinform..

[602]  Alvis Cheuk M. Fong,et al.  ASD-DiagNet: A Hybrid Learning Approach for Detection of Autism Spectrum Disorder Using fMRI Data , 2019, Front. Neuroinform..

[603]  Joshua M. Stuart,et al.  The Cancer Genome Atlas Pan-Cancer analysis project , 2013, Nature Genetics.

[604]  Xavier Bresson,et al.  Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering , 2016, NIPS.

[605]  Rolf Backofen,et al.  Combinatorial ensemble miRNA target prediction of co-regulation networks with non-prediction data , 2017, Nucleic acids research.

[606]  David W. Ritchie,et al.  PEPSI-Dock: a detailed data-driven protein-protein interaction potential accelerated by polar Fourier correlation , 2016, Bioinform..

[607]  Mike Steel,et al.  Phylogenomics with incomplete taxon coverage: the limits to inference , 2010, BMC Evolutionary Biology.

[608]  E. Domingo,et al.  RNA virus mutations and fitness for survival. , 1997, Annual review of microbiology.

[609]  Andrey Kazennov,et al.  The cornucopia of meaningful leads: Applying deep adversarial autoencoders for new molecule development in oncology , 2016, Oncotarget.

[610]  Yang Li,et al.  HMDD v2.0: a database for experimentally supported human microRNA and disease associations , 2013, Nucleic Acids Res..

[611]  A. Clatworthy,et al.  Targeting virulence: a new paradigm for antimicrobial therapy , 2007, Nature Chemical Biology.

[612]  Melissa M. Harrison,et al.  Mechanisms regulating zygotic genome activation , 2018, Nature Reviews Genetics.

[613]  H. Nakagawa,et al.  Whole genome sequencing analysis for cancer genomics and precision medicine , 2018, Cancer science.

[614]  Martin Hartmann,et al.  Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities , 2009, Applied and Environmental Microbiology.

[615]  D. Dey,et al.  Real-Time Adaptive Apnea and Hypopnea Event Detection Methodology for Portable Sleep Apnea Monitoring Devices , 2013, IEEE Transactions on Biomedical Engineering.

[616]  Dinggang Shen,et al.  Multiple-Network Classification of Childhood Autism Using Functional Connectivity Dynamics , 2014, MICCAI.

[617]  Chris P Ponting,et al.  Complexities of post-transcriptional regulation and the modeling of ceRNA crosstalk , 2018, Critical reviews in biochemistry and molecular biology.

[618]  Rebecca Saxe,et al.  Directed network discovery with dynamic network modelling , 2017, Neuropsychologia.

[619]  Vladimir A Mitkevich,et al.  Na,K-ATPase α-subunit conformation determines glutathionylation efficiency. , 2019, Biochemical and biophysical research communications.

[620]  Wentian Li,et al.  A Complete Enumeration and Classification of Two-Locus Disease Models , 1999, Human Heredity.

[621]  J Sühnel,et al.  More Hydrogen Bonds for the (structural) Biologist , 2022 .

[622]  Sorin Draghici,et al.  Down-weighting overlapping genes improves gene set analysis , 2012, BMC Bioinformatics.

[623]  Xing Chen,et al.  EGBMMDA: Extreme Gradient Boosting Machine for MiRNA-Disease Association prediction , 2018, Cell Death & Disease.

[624]  Juan M. Vaquerizas,et al.  Chromatin Architecture Emerges during Zygotic Genome Activation Independent of Transcription , 2017, Cell.

[625]  Réka Albert,et al.  Conserved network motifs allow protein-protein interaction prediction , 2004, Bioinform..

[626]  Dominique Ferrandon,et al.  Staufen protein associates with the 3′UTR of bicoid mRNA to form particles that move in a microtubule-dependent manner , 1994, Cell.

[627]  Kevin Murphy,et al.  Resting-state fMRI confounds and cleanup , 2013, NeuroImage.

[628]  M. Poptsova,et al.  Tissue-specific impact of stem-loops and quadruplexes on cancer breakpoints formation , 2019, BMC Cancer.

[629]  Minglei Ren,et al.  Trophic Status Is Associated With Community Structure and Metabolic Potential of Planktonic Microbiota in Plateau Lakes , 2019, Front. Microbiol..

[630]  Matteo Comin,et al.  Fast Computation of Entropic Profiles for the Detection of Conservation in Genomes , 2013, PRIB.

[631]  E. Conway,et al.  Role of the 2 zebrafish survivin genes in vasculo-angiogenesis, neurogenesis, cardiogenesis and hematopoiesis , 2009, BMC Developmental Biology.

[632]  Julien Riou,et al.  Interhuman transmissibility of Middle East respiratory syndrome coronavirus: estimation of pandemic risk , 2013, The Lancet.

[633]  Dmitriy Zhuk No-Rainbow Problem is NP-Hard , 2020, ArXiv.

[634]  Luay Nakhleh,et al.  Unifying Gene Duplication, Loss, and Coalescence on Phylogenetic Networks , 2019, bioRxiv.

[635]  O. Chahrour,et al.  Stable isotope labelling methods in mass spectrometry-based quantitative proteomics. , 2015, Journal of pharmaceutical and biomedical analysis.

[636]  Guido Davidzon,et al.  Mitochondrial DNA and disease , 2005, Annals of medicine.

[637]  ENCODEConsortium,et al.  An Integrated Encyclopedia of DNA Elements in the Human Genome , 2012, Nature.

[638]  Guigang Zhang,et al.  Deep Learning , 2016, Int. J. Semantic Comput..

[639]  Amera Almas,et al.  Enhancing the performance of decision tree: A research study of dealing with unbalanced data , 2012, Seventh International Conference on Digital Information Management (ICDIM 2012).

[640]  S. Bicciato,et al.  Comparison of computational methods for Hi-C data analysis , 2017, Nature Methods.

[641]  Jimmy Ba,et al.  Adam: A Method for Stochastic Optimization , 2014, ICLR.

[642]  Allam Appa Rao,et al.  G-IMEx: A comprehensive software tool for detection of microsatellites from genome sequences , 2010, Bioinformation.

[643]  Michael A. Bender,et al.  A General-Purpose Counting Filter: Making Every Bit Count , 2017, SIGMOD Conference.

[644]  Mike Steel,et al.  Terraces in Phylogenetic Tree Space , 2011, Science.