Exploring the Role of Small Molecules in Biological Systems Using Network Approaches

[1]  J. Zhang,et al.  Data mining reveals a network of early-response genes as a consensus signature of drug-induced in vitro and in vivo toxicity , 2013, The Pharmacogenomics Journal.

[2]  Alex J. Cornish,et al.  SANTA: Quantifying the Functional Content of Molecular Networks , 2014, PLoS Comput. Biol..

[3]  Qingsong Xu,et al.  Rcpi: R/Bioconductor package to generate various descriptors of proteins, compounds and their interactions , 2015, Bioinform..

[4]  Peter J. van der Spek,et al.  NetWeAvers: an R package for integrative biological network analysis with mass spectrometry data , 2013, Bioinform..

[5]  M E J Newman,et al.  Community structure in social and biological networks , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[6]  Svetlana Bureeva,et al.  Network and pathway analysis of compound-protein interactions. , 2009, Methods in molecular biology.

[7]  Rajarshi Guha,et al.  Structure-Activity Landscape Index: Identifying and Quantifying Activity Cliffs , 2008, J. Chem. Inf. Model..

[8]  Stefan Wetzel,et al.  Interactive exploration of chemical space with Scaffold Hunter. , 2009, Nature chemical biology.

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

[10]  Stefan Wetzel,et al.  Bioactivity-guided mapping and navigation of chemical space. , 2009, Nature chemical biology.

[11]  Haiyuan Yu,et al.  Target Essentiality and Centrality Characterize Drug Side Effects , 2013, PLoS Comput. Biol..

[12]  J. Bajorath,et al.  Structure-activity relationship anatomy by network-like similarity graphs and local structure-activity relationship indices. , 2008, Journal of medicinal chemistry.

[13]  A. Barabasi,et al.  Human symptoms–disease network , 2014, Nature Communications.

[14]  Tao Xu,et al.  Target Inhibition Networks: Predicting Selective Combinations of Druggable Targets to Block Cancer Survival Pathways , 2013, PLoS Comput. Biol..

[15]  S. Friend,et al.  A network view of disease and compound screening , 2009, Nature Reviews Drug Discovery.

[16]  Rajarshi Guha,et al.  Assessing How Well a Modeling Protocol Captures a Structure-Activity Landscape , 2008, J. Chem. Inf. Model..

[17]  John P. Overington,et al.  ChEMBL: a large-scale bioactivity database for drug discovery , 2011, Nucleic Acids Res..

[18]  J. Lehár,et al.  Synergistic drug combinations improve therapeutic selectivity , 2009, Nature Biotechnology.

[19]  Joel Dudley,et al.  Exploiting drug-disease relationships for computational drug repositioning , 2011, Briefings Bioinform..

[20]  A. Barabasi,et al.  The human disease network , 2007, Proceedings of the National Academy of Sciences.

[21]  Garry Robins,et al.  An introduction to exponential random graph (p*) models for social networks , 2007, Soc. Networks.

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

[23]  Xiang Zhang,et al.  Drug repositioning by integrating target information through a heterogeneous network model , 2014, Bioinform..

[24]  Rodrigo Dienstmann,et al.  Drug development to overcome resistance to EGFR inhibitors in lung and colorectal cancer , 2012, Molecular oncology.

[25]  Katritzky,et al.  Definition of Templates within Combinatorial Libraries. , 2000, Journal of combinatorial chemistry.

[26]  Salvatore Alaimo,et al.  Drug–target interaction prediction through domain-tuned network-based inference , 2013, Bioinform..

[27]  Tero Aittokallio,et al.  Predicting drug-target interactions through integrative analysis of chemogenetic assays in yeast. , 2013, Molecular bioSystems.

[28]  Peter Ertl,et al.  Mining for Bioactive Scaffolds with Scaffold Networks: Improved Compound Set Enrichment from Primary Screening Data , 2011, J. Chem. Inf. Model..

[29]  R. Tagliaferri,et al.  Discovery of drug mode of action and drug repositioning from transcriptional responses , 2010, Proceedings of the National Academy of Sciences.

[30]  Yasuo Tabei,et al.  Inferring protein domains associated with drug side effects based on drug-target interaction network , 2013, BMC Systems Biology.

[31]  G. Bemis,et al.  The properties of known drugs. 1. Molecular frameworks. , 1996, Journal of medicinal chemistry.

[32]  Miguel F Braña,et al.  Synthesis, antitumor activity, molecular modeling, and DNA binding properties of a new series of imidazonaphthalimides. , 2002, Journal of medicinal chemistry.

[33]  Rajarshi Guha,et al.  A survey of quantitative descriptions of molecular structure. , 2012, Current topics in medicinal chemistry.

[34]  Tobias Müller,et al.  Bioinformatics Applications Note Systems Biology Bionet: an R-package for the Functional Analysis of Biological Networks , 2022 .

[35]  P. Imming,et al.  Drugs, their targets and the nature and number of drug targets , 2006, Nature Reviews Drug Discovery.

[36]  S. Dudoit,et al.  Gains in Power from Structured Two-Sample Tests of Means on Graphs , 2010, 1009.5173.

[37]  Andrew I Su,et al.  HierS: hierarchical scaffold clustering using topological chemical graphs. , 2005, Journal of medicinal chemistry.

[38]  Matthias Dehmer,et al.  QuACN: an R package for analyzing complex biological networks quantitatively , 2011, Bioinform..

[39]  Matthias Dehmer,et al.  RMol: a toolset for transforming SD/Molfile structure information into R objects , 2012, Source Code for Biology and Medicine.

[40]  Tao Jiang,et al.  ChemmineR: a compound mining framework for R , 2008, Bioinform..

[41]  D. Altieri.  Survivin, cancer networks and pathway-directed drug discovery , 2008, Nature Reviews Cancer.

[42]  John A. Tallarico,et al.  Integrating high-content screening and ligand-target prediction to identify mechanism of action. , 2008, Nature chemical biology.

[43]  Damian Szklarczyk,et al.  STITCH 2: an interaction network database for small molecules and proteins , 2009, Nucleic Acids Res..

[44]  R. Sharan,et al.  PREDICT: a method for inferring novel drug indications with application to personalized medicine , 2011, Molecular systems biology.

[45]  Yasuo Tabei,et al.  Identification of chemogenomic features from drug–target interaction networks using interpretable classifiers , 2012, Bioinform..

[46]  Pankaj Agarwal,et al.  Combined Analysis of Phenotypic and Target-Based Screening in Assay Networks , 2014, Journal of biomolecular screening.

[47]  Julio Saez-Rodriguez,et al.  DvD: An R/Cytoscape pipeline for drug repurposing using public repositories of gene expression data , 2012, Bioinform..

[48]  Jian Su,et al.  Network-based analysis reveals distinct association patterns in a semantic MEDLINE-based drug-disease-gene network , 2014, Journal of Biomedical Semantics.

[49]  Fabian J. Theis,et al.  Structuring heterogeneous biological information using fuzzy clustering of k-partite graphs , 2010, BMC Bioinformatics.

[50]  Damian Szklarczyk,et al.  STRING v9.1: protein-protein interaction networks, with increased coverage and integration , 2012, Nucleic Acids Res..

[51]  Lei Huang,et al.  DrugComboRanker: drug combination discovery based on target network analysis , 2014, Bioinform..

[52]  Anne Mai Wassermann,et al.  SARANEA: A Freely Available Program To Mine Structure-Activity and Structure-Selectivity Relationship Information in Compound Data Sets , 2010, J. Chem. Inf. Model..

[53]  Peter Ertl,et al.  Compound Set Enrichment: A Novel Approach to Analysis of Primary HTS Data , 2010, J. Chem. Inf. Model..

[54]  Carter T. Butts,et al.  network: A Package for Managing Relational Data in R , 2008 .

[55]  Tapio Pahikkala,et al.  Toward more realistic drug^target interaction predictions , 2014 .

[56]  Yuhao Wang,et al.  Predicting drug-target interactions using restricted Boltzmann machines , 2013, Bioinform..

[57]  Krister Wennerberg,et al.  TIMMA-R: an R package for predicting synergistic multi-targeted drug combinations in cancer cell lines or patient-derived samples , 2015, Bioinform..

[58]  Michael P. Krein,et al.  Exploration of the topology of chemical spaces with network measures. , 2011, The journal of physical chemistry. A.

[59]  Gerald M. Maggiora,et al.  On Outliers and Activity Cliffs-Why QSAR Often Disappoints , 2006, J. Chem. Inf. Model..

[60]  L. Wodicka,et al.  Dual kinase-bromodomain inhibitors for rationally designed polypharmacology , 2014, Nature chemical biology.

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

[62]  Eugenio Uriarte,et al.  Alignment-free prediction of a drug-target complex network based on parameters of drug connectivity and protein sequence of receptors. , 2009, Molecular pharmaceutics.

[63]  J. Bajorath,et al.  SAR index: quantifying the nature of structure-activity relationships. , 2007, Journal of medicinal chemistry.

[64]  Gábor Csárdi,et al.  The igraph software package for complex network research , 2006 .

[65]  Russ B Altman,et al.  PharmGKB: the pharmacogenetics and pharmacogenomics knowledge base. , 2005, Methods in molecular biology.

[66]  A. Bauer-Mehren,et al.  Gene-Disease Network Analysis Reveals Functional Modules in Mendelian, Complex and Environmental Diseases , 2011, PloS one.

[67]  Martina Morris,et al.  statnet: Software Tools for the Representation, Visualization, Analysis and Simulation of Network Data. , 2008, Journal of statistical software.

[68]  P. Hajduk,et al.  Rational approaches to targeted polypharmacology: creating and navigating protein-ligand interaction networks. , 2010, Current opinion in chemical biology.

[69]  R. Iyengar,et al.  Systems approaches to polypharmacology and drug discovery. , 2010, Current opinion in drug discovery & development.

[70]  Steve Horvath,et al.  WGCNA: an R package for weighted correlation network analysis , 2008, BMC Bioinformatics.

[71]  Yun Xiao,et al.  Network Analysis Reveals Functional Cross-links between Disease and Inflammation Genes , 2013, Scientific Reports.

[72]  C. Steinbeck,et al.  Recent developments of the chemistry development kit (CDK) - an open-source java library for chemo- and bioinformatics. , 2006, Current pharmaceutical design.

[73]  A. Barabasi,et al.  A Protein–Protein Interaction Network for Human Inherited Ataxias and Disorders of Purkinje Cell Degeneration , 2006, Cell.

[74]  Michael J. Keiser,et al.  Large Scale Prediction and Testing of Drug Activity on Side-Effect Targets , 2012, Nature.

[75]  Jürgen Bajorath,et al.  Molecular Mechanism-Based Network-like Similarity Graphs Reveal Relationships between Different Types of Receptor Ligands and Structural Changes that Determine Agonistic, Inverse-Agonistic, and Antagonistic Effects , 2011, J. Chem. Inf. Model..

[76]  Hiroaki Kitano,et al.  The PANTHER database of protein families, subfamilies, functions and pathways , 2004, Nucleic Acids Res..

[77]  P. Shannon,et al.  Cytoscape: a software environment for integrated models of biomolecular interaction networks. , 2003, Genome research.

[78]  Samuel J. Webb,et al.  Self organising hypothesis networks: a new approach for representing and structuring SAR knowledge , 2014, Journal of Cheminformatics.

[79]  Xin Wu,et al.  Drug repositioning by applying 'expression profiles' generated by integrating chemical structure similarity and gene semantic similarity. , 2014, Molecular bioSystems.

[80]  L. Peshkin,et al.  Exploiting polypharmacology for drug target deconvolution , 2014, Proceedings of the National Academy of Sciences.

[81]  W. Crumb,et al.  Blockade of multiple human cardiac potassium currents by the antihistamine terfenadine: possible mechanism for terfenadine-associated cardiotoxicity. , 1995, Molecular pharmacology.

[82]  Lang Li,et al.  Exploring a structural protein-drug interactome for new therapeutics in lung cancer. , 2014, Molecular bioSystems.

[83]  A. Barabasi,et al.  Drug—target network , 2007, Nature Biotechnology.

[84]  Qiang Huang,et al.  Corbi: a new R package for biological network alignment and querying , 2013, BMC Systems Biology.

[85]  Xing Chen,et al.  Drug-target interaction prediction by random walk on the heterogeneous network. , 2012, Molecular bioSystems.

[86]  Stefan Wetzel,et al.  The Scaffold Tree - Visualization of the Scaffold Universe by Hierarchical Scaffold Classification , 2007, J. Chem. Inf. Model..

[87]  J. Chen,et al.  Systems biology visualization tools for drug target discovery , 2010, Expert opinion on drug discovery.

[88]  William Pao,et al.  Identifying genotype-dependent efficacy of single and combined PI3K- and MAPK-pathway inhibition in cancer , 2009, Proceedings of the National Academy of Sciences.

[89]  Jinwoo Kim,et al.  An integrative model of multi-organ drug-induced toxicity prediction using gene-expression data , 2014, BMC Bioinformatics.

[90]  Michael M. Hann,et al.  RECAP-Retrosynthetic Combinatorial Analysis Procedure: A Powerful New Technique for Identifying Privileged Molecular Fragments with Useful Applications in Combinatorial Chemistry , 1998, J. Chem. Inf. Comput. Sci..

[91]  Hongyu Zhao,et al.  FacPad: Bayesian sparse factor modeling for the inference of pathways responsive to drug treatment , 2012, Bioinform..

[92]  Rajarshi Guha,et al.  Chemical Informatics Functionality in R , 2007 .

[93]  Sandrine Dudoit,et al.  More power via graph-structured tests for differential expression of gene networks , 2012, 1206.6980.

[94]  Yong Wang,et al.  Network predicting drug's anatomical therapeutic chemical code , 2013, Bioinform..

[95]  Dapeng Hao,et al.  Prioritizing candidate disease-related long non-coding RNAs by walking on the heterogeneous lncRNA and disease network. , 2015, Molecular bioSystems.

[96]  S. Giordano,et al.  ReviewMolecular mechanisms of acquired resistance to tyrosine kinase targeted therapy , 2015 .

[97]  S Joshua Swamidass,et al.  Automatically Detecting Workflows in PubChem , 2012, Journal of biomolecular screening.