Predicting essential genes and proteins based on machine learning and network topological features: A comprehensive review

Frontiers in Physiology

Volumn 7, Issue MAR, 2016, Pages

  Zhang, Xue ^a   Acencio, Marcio Luis ^b,c   Lemke, Ney ^b  

^a XIANGNAN UNIVERSITY   (China)

^b SÃO PAULO STATE UNIVERSITY UNESP   (Brazil)

^c NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Norway)

Author keywords

Essential genes proteins; Machine learning; Network topological features; Prediction models; Systems biology

Indexed keywords

PROTEIN;

AREA UNDER THE CURVE; ASPERGILLUS FUMIGATUS; BACILLUS SUBTILIS; BAYESIAN LEARNING; CLASSIFICATION ALGORITHM; ESCHERICHIA COLI; ESSENTIAL GENE; GENE EXPRESSION PROFILING; GENE IDENTIFICATION; HUMAN; INFORMATION PROCESSING; MACHINE LEARNING; MEASUREMENT ACCURACY; MEASUREMENT PRECISION; NETWORK TOPOLOGICAL FEATURE; NEUROSPORA CRASSA; NONHUMAN; PROTEIN PROTEIN INTERACTION; PSEUDOMONAS AERUGINOSA; RECEIVER OPERATING CHARACTERISTIC; REVIEW; SCHIZOSACCHAROMYCES POMBE; STREPTOCOCCUS SANGUINIS; SUPPORT VECTOR MACHINE; TASK PERFORMANCE;

EID: 84964679066     PISSN: None     EISSN: 1664042X     Source Type: Journal    
DOI: 10.3389/fphys.2016.00075     Document Type: Review

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