A new machine learning approach for protein phosphorylation site prediction in plants

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 5462 LNBI, Issue , 2009, Pages 18-29

  Gao, Jianjiong ^a,b   Agrawal, Ganesh Kumar ^b,c   Thelen, Jay J ^b,c   Obradovic, Zoran ^d   Dunker, A Keith ^e   Xu, Dong ^a,b  

^a Department of Computer Science ^*  (United States)

^b UNIVERSITY OF MISSOURI   (United States)

^c University of Missouri   (United States)

^d TEMPLE UNIVERSITY   (United States)

^e Indiana University   (United States)

Author keywords

Arabidopsis; KNN; Phosphoproteomics; Protein Disorder; Protein phosphorylation; SVM

Indexed keywords

ARABIDOPSIS; KNN; PHOSPHOPROTEOMICS; PROTEIN PHOSPHORYLATION; SVM;

BIOINFORMATICS; BIOLOGY; LEARNING ALGORITHMS; MASS SPECTROMETRY; ROBOT LEARNING; STATISTICAL TESTS; SUPPORT VECTOR MACHINES;

PHOSPHORYLATION;

EID: 68249084742     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-642-00727-9_4     Document Type: Conference Paper

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