Computational identification of human long intergenic non-coding RNAs using a GA-SVM algorithm

Gene

Volumn 533, Issue 1, 2014, Pages 94-99

  Wang, Yanqiu ^a   Li, Yang ^b   Wang, Qi ^c   Lv, Yingli ^a   Wang, Shiyuan ^a   Chen, Xi ^a   Yu, Xuexin ^a   Jiang, Wei ^a   Li, Xia ^a  

^a HARBIN MEDICAL UNIVERSITY   (China)

^b Special Police Academy of China   (China)

^c GUANGDONG UNIVERSITY OF TECHNOLOGY   (China)

Author keywords

Classification; Feature selection; GA SVM; LincRNAs

Indexed keywords

LONG UNTRANSLATED RNA;

ARTICLE; CONTROLLED STUDY; GENE EXPRESSION; GENETIC ALGORITHM; HUMAN; HUMAN CELL; HUMAN TISSUE; MOLECULAR RECOGNITION; PRIORITY JOURNAL; PROTEIN SECONDARY STRUCTURE; SUPPORT VECTOR MACHINE;

A WRAPPER FEATURE SELECTION ALGORITHM THAT COMBINES SUPPORT VECTOR MACHINE AND GENETIC ALGORITHM; ACC; ACCURACY; CLASSIFICATION; CORRELATION COEFFICIENT; F-MEASURE; FEATURE SELECTION; FM; GA; GA-SVM; GENETIC ALGORITHM; LINC-SF; LINCRNAS; LNCRNAS; LONG INTERGENIC NON-CODING RNAS; LONG NON-CODING RNAS; MCC; MFE; MICRORNA PRECURSORS; MINIMUM FREE ENERGY; PRE-MIRNAS; SE; SENSITIVITY; SP; SPECIFICITY; SUPPORT VECTOR MACHINE; SVM; THE LINCRNA CLASSIFIER BASED ON SELECTED FEATURES;

ALGORITHMS; COMPUTATIONAL BIOLOGY; HUMANS; REPRODUCIBILITY OF RESULTS; RNA, UNTRANSLATED; SUPPORT VECTOR MACHINES;

EID: 84887233614     PISSN: 03781119     EISSN: 18790038     Source Type: Journal    
DOI: 10.1016/j.gene.2013.09.118     Document Type: Article

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