Prediction of Protein–Protein Interaction Sites with Machine-Learning-Based Data-Cleaning and Post-Filtering Procedures

Journal of Membrane Biology

Volumn 249, Issue 1-2, 2016, Pages 141-153

  Liu, Guang Hui ^a,b   Shen, Hong Bin ^c   Yu, Dong Jun ^a  

^a NANJING UNIVERSITY OF SCIENCE AND TECHNOLOGY   (China)

^b NANJING UNIVERSITY OF FINANCE AND ECONOMICS   (China)

^c SHANGHAI JIAO TONG UNIVERSITY   (China)

Author keywords

Data cleaning; Imbalanced learning; Post filtering; Protein protein interaction sites; Random forests

Indexed keywords

ACCURACY; ALGORITHM; AMINO ACID SEQUENCE; ARTICLE; COMPLEX FORMATION; CORRELATION COEFFICIENT; DATA CLEANING; DATA PROCESSING; FALSE POSITIVE RESULT; MACHINE LEARNING; POSITION WEIGHT MATRIX; POST FILTERING; PREDICTION; PROTEIN ANALYSIS; PROTEIN PROTEIN INTERACTION; RANDOM FOREST; SEQUENCE ALIGNMENT; X RAY CRYSTALLOGRAPHY; BINDING SITE; BIOLOGY; CHEMISTRY; METABOLISM; MOLECULAR MODEL; PROCEDURES; PROTEIN CONFORMATION; PROTEIN DATABASE; REPRODUCIBILITY; WORKFLOW;

PROTEIN; PROTEIN BINDING;

BINDING SITES; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; MACHINE LEARNING; MODELS, MOLECULAR; PROTEIN BINDING; PROTEIN CONFORMATION; PROTEIN INTERACTION MAPPING; PROTEINS; REPRODUCIBILITY OF RESULTS; WORKFLOW;

EID: 84946867095     PISSN: 00222631     EISSN: 14321424     Source Type: Journal    
DOI: 10.1007/s00232-015-9856-z     Document Type: Article

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