Different protein-protein interface patterns predicted by different machine learning methods.

scientific article published on 22 November 2017

Different protein-protein interface patterns predicted by different machine learning methods. is …
instance of (P31):
scholarly articleQ13442814

External links are
P819ADS bibcode2017NatSR...716023W
P6179Dimensions Publication ID1092730443
P356DOI10.1038/S41598-017-16397-Z
P8608Fatcat IDrelease_7mv23iucmvcunghe67uryfpiuu
P932PMC publication ID5700192
P698PubMed publication ID29167570

P50authorXinqi GongQ88143779
P2093author name stringWei Wang
Jianxin Yin
Yongxiao Yang
P2860cites workInformation assessment on predicting protein-protein interactionsQ24796950
Computational prediction of protein interfaces: A review of data driven methodsQ26783912
Principles of protein-protein interactionsQ27860855
Prediction of protein-protein interaction sites in sequences and 3D structures by random forestsQ28474551
Progress and challenges in predicting protein interfacesQ28602320
Predicting protein-protein interactions from primary protein sequences using a novel multi-scale local feature representation scheme and the random forestQ30648471
Evaluation of different biological data and computational classification methods for use in protein interaction predictionQ31031427
Partner-aware prediction of interacting residues in protein-protein complexes from sequence dataQ31043905
A comparative study of different machine learning methods on microarray gene expression dataQ31150616
Support vector machines and kernels for computational biologyQ33381579
Principles of protein-protein recognitionQ33954341
Updates to the Integrated Protein-Protein Interaction Benchmarks: Docking Benchmark Version 5 and Affinity Benchmark Version 2.Q34487825
PAIRpred: partner-specific prediction of interacting residues from sequence and structureQ35045263
Learning interactions via hierarchical group-lasso regularizationQ36446528
History of protein-protein interactions: from egg-white to complex networksQ38019869
Predicting protein interface residues using easily accessible on-line resources.Q38386937
Predicting Protein-Protein Interactions from the Molecular to the Proteome LevelQ38807305
Predicting protein--protein interactions from primary structureQ40710149
Diffusion kernel-based logistic regression models for protein function predictionQ45158942
Prediction of protein-protein interaction sites using support vector machinesQ47869771
Prediction of protein-protein interactions using random decision forest frameworkQ48470497
The Key–Lock Theory and the Induced Fit TheoryQ56144898
Sequence-based prediction of protein-protein interaction sites with L1-logreg classifierQ87212279
Random ForestsQ115707260
P275copyright licenseCreative Commons Attribution 4.0 InternationalQ20007257
P6216copyright statuscopyrightedQ50423863
P433issue1
P407language of work or nameEnglishQ1860
P921main subjectmachine learningQ2539
P304page(s)16023
P577publication date2017-11-22
P1433published inScientific ReportsQ2261792
P1476titleDifferent protein-protein interface patterns predicted by different machine learning methods
P478volume7

Reverse relations

cites work (P2860)
Q99724618A Two-Layer SVM Ensemble-Classifier to Predict Interface Residue Pairs of Protein Trimers
Q57281082Neurocardiac regulation: From cardiac mechanisms to novel therapeutic approaches
Q57031875Pattern to Knowledge: Deep Knowledge-Directed Machine Learning for Residue-Residue Interaction Prediction