Review and comparative assessment of sequence‐based predictors of protein‐binding residues
暂无分享,去创建一个
[1] Zhu-Hong You,et al. Predicting Protein-Protein Interactions from Primary Protein Sequences Using a Novel Multi-Scale Local Feature Representation Scheme and the Random Forest , 2015, PloS one.
[2] Jun Hu,et al. Enhancing protein-vitamin binding residues prediction by multiple heterogeneous subspace SVMs ensemble , 2014, BMC Bioinformatics.
[3] J H Jia,et al. Prediction of protein-protein interactions using chaos game representation and wavelet transform via the random forest algorithm. , 2015, Genetics and molecular research : GMR.
[4] De-Shuang Huang,et al. Predicting protein–protein interactions from sequence using correlation coefficient and high-quality interaction dataset , 2010, Amino Acids.
[5] Aleksey A. Porollo,et al. Prediction‐based fingerprints of protein–protein interactions , 2006, Proteins.
[6] María Martín,et al. UniProt: A hub for protein information , 2015 .
[7] Xue-wen Chen,et al. Sequence-based prediction of protein interaction sites with an integrative method , 2009, Bioinform..
[8] Xiuquan Du,et al. Improved Prediction of Protein Binding Sites from Sequences Using Genetic Algorithm , 2009, The protein journal.
[9] Jing-Yu Yang,et al. Protein-protein interaction sites prediction by ensembling SVM and sample-weighted random forests , 2016, Neurocomputing.
[10] Leo Breiman,et al. Random Forests , 2001, Machine Learning.
[11] Olivier Sperandio. Editorial: Toward the design of drugs on protein-protein interactions. , 2012, Current pharmaceutical design.
[12] Daniel R. Caffrey,et al. Are protein–protein interfaces more conserved in sequence than the rest of the protein surface? , 2004, Protein science : a publication of the Protein Society.
[13] Jean-Christophe Nebel,et al. Progress and challenges in predicting protein interfaces , 2015, Briefings Bioinform..
[14] Burkhard Rost,et al. ISIS: interaction sites identified from sequence , 2007, Bioinform..
[15] Zhiping Weng,et al. Evaluating template-based and template-free protein-protein complex structure prediction , 2014, Briefings Bioinform..
[16] J. Rodrigues,et al. Integrative computational modeling of protein interactions , 2014, The FEBS journal.
[17] Albert Chan,et al. PIPE: a protein-protein interaction prediction engine based on the re-occurring short polypeptide sequences between known interacting protein pairs , 2006, BMC Bioinformatics.
[18] Jun Hu,et al. TargetATPsite: A template‐free method for ATP‐binding sites prediction with residue evolution image sparse representation and classifier ensemble , 2013, J. Comput. Chem..
[19] Zhu-Hong You,et al. Prediction of protein-protein interactions from amino acid sequences with ensemble extreme learning machines and principal component analysis , 2013, BMC Bioinformatics.
[20] Zhu-Hong You,et al. Detecting Protein-Protein Interactions with a Novel Matrix-Based Protein Sequence Representation and Support Vector Machines , 2015, BioMed research international.
[21] Chen Xu,et al. Computational prediction of DNA-protein interactions: a review. , 2010, Current computer-aided drug design.
[22] Juwen Shen,et al. Predicting protein–protein interactions based only on sequences information , 2007, Proceedings of the National Academy of Sciences.
[23] David W Ritchie,et al. Recent progress and future directions in protein-protein docking. , 2008, Current protein & peptide science.
[24] L. Castagnoli,et al. mentha: a resource for browsing integrated protein-interaction networks , 2013, Nature Methods.
[25] Menglong Li,et al. PRED_PPI: a server for predicting protein-protein interactions based on sequence data with probability assignment , 2010, BMC Research Notes.
[26] Yong Zhou,et al. Ens-PPI: A Novel Ensemble Classifier for Predicting the Interactions of Proteins Using Autocovariance Transformation from PSSM , 2016, BioMed research international.
[27] Zhu-Hong You,et al. Using the Relevance Vector Machine Model Combined with Local Phase Quantization to Predict Protein-Protein Interactions from Protein Sequences , 2016, BioMed research international.
[28] Keith C. C. Chan,et al. Discovering Variable-Length Patterns in Protein Sequences for Protein-Protein Interaction Prediction , 2015, IEEE Transactions on NanoBioscience.
[29] Alan Wee-Chung Liew,et al. Sequence‐based prediction of protein–peptide binding sites using support vector machine , 2016, J. Comput. Chem..
[30] Yanzhi Guo,et al. Using support vector machine combined with auto covariance to predict protein–protein interactions from protein sequences , 2008, Nucleic acids research.
[31] The Uniprot Consortium,et al. UniProt: a hub for protein information , 2014, Nucleic Acids Res..
[32] Vasant G Honavar,et al. Computational prediction of protein interfaces: A review of data driven methods , 2015, FEBS letters.
[33] J. Bujnicki,et al. Computational methods for prediction of protein-RNA interactions. , 2012, Journal of structural biology.
[34] Yang Zhang,et al. BioLiP: a semi-manually curated database for biologically relevant ligand–protein interactions , 2012, Nucleic Acids Res..
[35] Vasant Honavar,et al. HomPPI: a class of sequence homology based protein-protein interface prediction methods , 2011, BMC Bioinformatics.
[36] Zhen Ji,et al. Prediction of protein-protein interactions from amino acid sequences using a novel multi-scale continuous and discontinuous feature set , 2014, BMC Bioinformatics.
[37] Keehyoung Joo,et al. proteins STRUCTURE O FUNCTION O BIOINFORMATICS SANN: Solvent accessibility prediction of proteins , 2022 .
[38] Hong-Bin Shen,et al. Prediction of Protein–Protein Interaction Sites with Machine-Learning-Based Data-Cleaning and Post-Filtering Procedures , 2015, The Journal of Membrane Biology.
[39] Naoki Orii,et al. Wiki-Pi: A Web-Server of Annotated Human Protein-Protein Interactions to Aid in Discovery of Protein Function , 2012, PloS one.
[40] Alfonso Valencia,et al. Progress and challenges in predicting protein-protein interaction sites , 2008, Briefings Bioinform..
[41] Paolo Frasconi,et al. Predicting Metal-Binding Sites from Protein Sequence , 2012, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[42] Tobias Hamp,et al. Sequence-based prediction of protein-protein interactions , 2014 .
[43] Christopher J. C. Burges,et al. A Tutorial on Support Vector Machines for Pattern Recognition , 1998, Data Mining and Knowledge Discovery.
[44] Yang Zhang,et al. Protein-protein complex structure predictions by multimeric threading and template recombination. , 2011, Structure.
[45] Lukasz A. Kurgan,et al. DFLpred: High-throughput prediction of disordered flexible linker regions in protein sequences , 2016, Bioinform..
[46] Petras J. Kundrotas,et al. Accuracy of Protein-Protein Binding Sites in High-Throughput Template-Based Modeling , 2010, PLoS Comput. Biol..
[47] Burkhard Rost,et al. Evolutionary profiles improve protein-protein interaction prediction from sequence , 2015, Bioinform..
[48] Rod K. Nibbe,et al. Protein–protein interaction networks and subnetworks in the biology of disease , 2011, Wiley interdisciplinary reviews. Systems biology and medicine.
[49] Ashkan Golshani,et al. Binding Site Prediction for Protein-Protein Interactions and Novel Motif Discovery using Re-occurring Polypeptide Sequences , 2011, BMC Bioinformatics.
[50] Vasant Honavar,et al. Protein-RNA interface residue prediction using machine learning: an assessment of the state of the art , 2012, BMC Bioinformatics.
[51] Darby Tien-Hao Chang,et al. Predicting protein-protein interactions in unbalanced data using the primary structure of proteins , 2010, BMC Bioinformatics.
[52] Sheng-You Huang,et al. Search strategies and evaluation in protein-protein docking: principles, advances and challenges. , 2014, Drug discovery today.
[53] Ruth Nussinov,et al. An overview of recent advances in structural bioinformatics of protein-protein interactions and a guide to their principles. , 2014, Progress in biophysics and molecular biology.
[54] K. Mizuguchi,et al. Partner-Aware Prediction of Interacting Residues in Protein-Protein Complexes from Sequence Data , 2011, PloS one.
[55] Xing Chen,et al. Sequence-based prediction of protein-protein interactions using weighted sparse representation model combined with global encoding , 2016, BMC Bioinformatics.
[56] Yu Liu,et al. Prediction of Protein-Protein Interaction Sites Based on Naive Bayes Classifier , 2015, Biochemistry research international.
[57] Gajendra P. S. Raghava,et al. Prediction of vitamin interacting residues in a vitamin binding protein using evolutionary information , 2013, BMC Bioinformatics.
[58] R. Nagarajan,et al. Novel approach for selecting the best predictor for identifying the binding sites in DNA binding proteins , 2013, Nucleic acids research.
[59] Michal Brylinski,et al. Predicting protein interface residues using easily accessible on-line resources , 2015, Briefings Bioinform..
[60] Christopher L. McClendon,et al. Reaching for high-hanging fruit in drug discovery at protein–protein interfaces , 2007, Nature.
[61] Olivier Sperandio,et al. Editorial: [Hot Topics: Toward the Design of Drugs on Protein-Protein Interactions] , 2012 .
[62] Philip E. Bourne,et al. The Protein Data Bank (PDB) | NIST , 2002 .
[63] Juan Fernández-Recio,et al. Prediction of protein binding sites and hot spots , 2011 .
[64] Raphael A. G. Chaleil,et al. Updates to the Integrated Protein-Protein Interaction Benchmarks: Docking Benchmark Version 5 and Affinity Benchmark Version 2. , 2015, Journal of molecular biology.
[65] Abdulaziz Yousef,et al. A novel method based on new adaptive LVQ neural network for predicting protein-protein interactions from protein sequences. , 2013, Journal of theoretical biology.
[66] Hong Yan,et al. Fast prediction of protein-protein interaction sites based on Extreme Learning Machines , 2014, Neurocomputing.
[67] Kaustubh D. Dhole,et al. SPRINGS: Prediction of Protein- Protein Interaction Sites Using Artificial Neural Networks , 2014 .
[68] Bin Liu,et al. SPPS: A Sequence-Based Method for Predicting Probability of Protein-Protein Interaction Partners , 2012, PloS one.
[69] Jing-Yu Yang,et al. A Cascade Random Forests Algorithm for Predicting Protein-Protein Interaction Sites , 2015, IEEE Transactions on NanoBioscience.
[70] Jinyan Li,et al. Sequence-based identification of interface residues by an integrative profile combining hydrophobic and evolutionary information , 2010, BMC Bioinformatics.
[71] Lukasz Kurgan,et al. Structural protein descriptors in 1-dimension and their sequence-based predictions. , 2011, Current protein & peptide science.
[72] Kuo-Chen Chou,et al. iPPBS-Opt: A Sequence-Based Ensemble Classifier for Identifying Protein-Protein Binding Sites by Optimizing Imbalanced Training Datasets , 2016, Molecules.
[73] Zhu-Hong You,et al. Using Weighted Sparse Representation Model Combined with Discrete Cosine Transformation to Predict Protein-Protein Interactions from Protein Sequence , 2015, BioMed research international.
[74] Lukasz A. Kurgan,et al. A comprehensive comparative review of sequence-based predictors of DNA- and RNA-binding residues , 2016, Briefings Bioinform..
[75] Daniel B. Roche,et al. Proteins and Their Interacting Partners: An Introduction to Protein–Ligand Binding Site Prediction Methods , 2015, International journal of molecular sciences.
[76] J. De las Rivas,et al. Protein-protein interaction networks: unraveling the wiring of molecular machines within the cell. , 2012, Briefings in functional genomics.
[77] Oriol Fornes,et al. On the use of knowledge-based potentials for the evaluation of models of protein-protein, protein-DNA, and protein-RNA interactions. , 2014, Advances in protein chemistry and structural biology.
[78] Reza Ebrahimpour,et al. PPIevo: protein-protein interaction prediction from PSSM based evolutionary information. , 2013, Genomics.
[79] Jan Tavernier,et al. Modulation of Protein–Protein Interactions for the Development of Novel Therapeutics , 2015, Molecular therapy : the journal of the American Society of Gene Therapy.
[80] Liam J. McGuffin,et al. The PSIPRED protein structure prediction server , 2000, Bioinform..
[81] Bogdan Istrate,et al. Algorithmic approaches to protein-protein interaction site prediction , 2015, Algorithms for Molecular Biology.
[82] Bin Xia,et al. PETs: A Stable and Accurate Predictor of Protein-Protein Interacting Sites Based on Extremely-Randomized Trees , 2015, IEEE Transactions on NanoBioscience.
[83] Kenji Mizuguchi,et al. Applying the Naïve Bayes classifier with kernel density estimation to the prediction of protein-protein interaction sites , 2010, Bioinform..
[84] En-Shiun Annie Lee,et al. Prediction of Protein-Protein Interaction via co-occurring Aligned Pattern Clusters. , 2016, Methods.
[85] Jun Hu,et al. Designing Template-Free Predictor for Targeting Protein-Ligand Binding Sites with Classifier Ensemble and Spatial Clustering , 2013, IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[86] Lukasz A. Kurgan,et al. Prediction and analysis of nucleotide-binding residues using sequence and sequence-derived structural descriptors , 2012, Bioinform..
[87] Ke Chen,et al. Investigation of Atomic Level Patterns in Protein—Small Ligand Interactions , 2009, PloS one.
[88] Xingming Zhao,et al. Predicting protein–protein interactions from protein sequences using meta predictor , 2010, Amino Acids.
[89] Lukasz Kurgan,et al. High-throughput prediction of RNA, DNA and protein binding regions mediated by intrinsic disorder , 2015, Nucleic acids research.
[90] Janet M Thornton,et al. Protein-DNA interactions: amino acid conservation and the effects of mutations on binding specificity. , 2002, Journal of molecular biology.
[91] Yangchao Huang,et al. Simple sequence-based kernels do not predict protein-protein interactions , 2010, Bioinform..
[92] Ram Samudrala,et al. A protein sequence meta-functional signature for calcium binding residue prediction , 2010, Pattern Recognit. Lett..
[93] A. Emili,et al. Protein-protein interaction networks: probing disease mechanisms using model systems , 2013, Genome Medicine.
[94] K. Kinoshita,et al. Hub Promiscuity in Protein-Protein Interaction Networks , 2010, International journal of molecular sciences.
[95] Tuo Zhang,et al. Analysis and prediction of RNA-binding residues using sequence, evolutionary conservation, and predicted secondary structure and solvent accessibility. , 2010, Current protein & peptide science.
[96] Darby Tien-Hao Chang,et al. Predicting the protein-protein interactions using primary structures with predicted protein surface , 2010, BMC Bioinformatics.
[97] Hong-Bin Shen,et al. Adaptive compressive learning for prediction of protein-protein interactions from primary sequence. , 2011, Journal of theoretical biology.