isGPT: An optimized model to identify sub-Golgi protein types using SVM and Random Forest based feature selection

Artificial Intelligence in Medicine

Volumn 84, Issue , 2018, Pages 90-100

  Rahman, M Saifur ^a   Rahman, Md Khaledur ^b   Kaykobad, M ^a   Rahman, M Sohel ^a  

^a BANGLADESH UNIVERSITY OF ENGINEERING AND TECHNOLOGY   (Bangladesh)

^b INDIANA UNIVERSITY   (United States)

Author keywords

Classification; Random Forest; Regression; Sub Golgi Apparatus; Support vector machine

Indexed keywords

CELL MEMBRANES; CLASSIFICATION (OF INFORMATION); DECISION TREES; FEATURE EXTRACTION; IMAGE RETRIEVAL; NEURODEGENERATIVE DISEASES; PROTEINS; REGRESSION ANALYSIS; SUPPORT VECTOR MACHINES;

10-FOLD CROSS-VALIDATION; CLASSIFICATION MODELS; ENDOPLASMIC RETICULUM; GOLGI APPARATUS; RANDOM FORESTS; REGRESSION; STATE-OF-THE-ART TECHNIQUES; SYNTHETIC MINORITY OVER-SAMPLING TECHNIQUES;

BIOSYNTHESIS;

DIPEPTIDE DERIVATIVE; N GAPPED DIPEPTIDE; PROTEIN; SUB GOLGI PROTEIN; TRIPEPTIDE DERIVATIVE; UNCLASSIFIED DRUG; OLIGOPEPTIDE;

ACCURACY; AMINO ACID COMPOSITION; AMINO ACID SEQUENCE; ARTICLE; COMPARATIVE STUDY; CONTROLLED STUDY; CORRELATION COEFFICIENT; GOLGI COMPLEX; PRIORITY JOURNAL; PROTEIN ANALYSIS; PROTEIN LOCALIZATION; RANDOM FOREST; SUPPORT VECTOR MACHINE; ANIMAL; BIOLOGY; CHEMISTRY; CLASSIFICATION; HUMAN; PROCEDURES; PROTEIN DATABASE; REPRODUCIBILITY;

AMINO ACID SEQUENCE; ANIMALS; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; GOLGI APPARATUS; HUMANS; OLIGOPEPTIDES; PROTEINS; REPRODUCIBILITY OF RESULTS; SUPPORT VECTOR MACHINE;

EID: 85034849205     PISSN: 09333657     EISSN: 18732860     Source Type: Journal    
DOI: 10.1016/j.artmed.2017.11.003     Document Type: Article

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