Supervised learning method for the prediction of subcellular localization of proteins using amino acid and amino acid pair composition

BMC Genomics

Volumn 9, Issue SUPPL. 1, 2008, Pages

  Habib, Tanwir ^a   Zhang, Chaoyang ^b   Yang, Jack Y ^c   Qu, Mary Qu ^d   Deng, Youping ^a  

^a The University of Southern Mississippi   (United States)

^b UNIVERSITY OF SOUTHERN MISSISSIPPI   (United States)

^c HARVARD MEDICAL SCHOOL   (United States)

^d NATIONAL HUMAN GENOME RESEARCH INSTITUTE   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AMINO ACID; PROTEIN DERIVATIVE; PROTEIN;

ACCURACY; AMINO ACID ANALYSIS; AMINO ACID COMPOSITION; AMINO ACID SEQUENCE; ARTICLE; BASE PAIRING; CONTROLLED STUDY; INTERMETHOD COMPARISON; KERNEL METHOD; MATHEMATICAL COMPUTING; PREDICTION; PROTEIN DETERMINATION; PROTEIN LOCALIZATION; RADIAL BASED FUNCTION; SIMULATION; SUPPORT VECTOR MACHINE; SWISS-PROT; VALIDATION PROCESS; ALGORITHM; BIOLOGY; CELL FRACTIONATION; CHEMISTRY; METABOLISM; METHODOLOGY; PROTEIN DATABASE;

ALGORITHMS; AMINO ACID SEQUENCE; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; PROTEINS; SUBCELLULAR FRACTIONS;

EID: 44449101758     PISSN: None     EISSN: 14712164     Source Type: Journal    
DOI: 10.1186/1471-2164-9-S1-S16     Document Type: Article

References (22)

1. Eisenhaber F Bork P Wanted: Subcellular localization of proteins based on sequence Trends in Cell Biology 1998, 8:169-170 10.1016/ S0962-8924(98)01226-4 9695832
2. Emanuelsson O Brunak S von Heijne G Locating proteins in the cell using TargetP, SignalP, and related tools Nature Protocols 2 2007:953-971 10.1038/nprot.2007.131
3. Claros MG Brunak S von Heijne G Prediction of N-terminal protein sorting signals Curr Opin Struct Biol 1997, 7:394-398 10.1016/ S0959-440X(97)80057-7 9204282
4. Reinhardt A Hubbard T Using neural networks for prediction of the subcellular location of proteins Nucleic Acids Res 1998, 26:2230-2236 147531 9547285 10.1093/nar/26.9.2230
5. Von Heijne G A new method for predicting sequence cleavage site Nucleic Acids Res 1986, 14:4683-4690 10.1093/nar/14.11.4683 3714490 311474
6. Blobel G Extraction from free ribosomes of a factor mediating ribosome detachment from rough microsomes Biochem Biophys Res Commun 1976, 68:1-7 10.1016/0006-291X(76)90001-2 1247447
7. Nakashima H Nishikawa K Discrimination of intracellular and extracellular proteins using amino-acid-composition and residue-pair frequencies J Mol Biol 1994, 238:54-61 10.1006/jmbi.1994.1267 8145256
8. Chou KC Elrod D Protein subcellular location prediction Protein Eng 1999, 12:107-118 10.1093/protein/12.2.107 10195282
9. Zhou ZH Jiang Y NeC4.5: Neural ensemble based C4.5 IEEE Transactions on Knowledge and Data Engineering 2004, 16(6):770-773 10.1109/TKDE.2004.11
10. Cortes C Vapnik V Support vector networks Mach Learn 1995, 20:273-293
11. Vapnik V The nature of Statistical Learning Theory Springer, New York 1995 8555380
12. Vapnik V Statistical Learning Theory Wiley, New York 1998
13. Park KJ Kanehisa M Prediction of protein subcellular locations by support vector machines using compositions of amino acids and amino acid pairs Bioinformatics 2003, 19(13):1656-1663 12967962 10.1093/ bioinformatics/btg222
14. Hua S Sun Z Support vector machine approach for protein subcellular localization prediction Bioinformatics 2001, 17:721-728 10.1093/ bioinformatics/17.8.721 11524373
15. Rumelhart D Hinton G Williams R Learning internal representations by error propagation Parallel Distributed Processing: Explorations in the microstructure of cognition 1986, 1:318-363
16. Kodratoff Y Nédellec C Working Noted of the IJCAI-95 Workshop on Machine Learning and Comprehensibility 1995
17. Bairoch A Apweiler R The SWISS-PROT protein sequence data bank and its supplement TrEMBL Nucleic Acids Res 1997, 28:45-48 10.1093/nar/28.1.45
18. Altschul SF Gish W Miller W Myers EW Lipman DJ Basic local alignment search tool J Mol Biol 1990, 215:403-410 2231712
19. Quinlan JR C4.5: Programs for Machine Learning Morgan Kaufmann Publishers, inc. Los Altos. California 1993
20. Winston P "Learning by Building Identification Trees", P. Winston, Artificial Intelligence, Addison-Wesley Publishing Company 1992:423-442
21. Bhasin M Raghava GP ESLpred: SVMachine-based method for subcellular localization of eukaryotic proteins using dipeptide compositions and PSI-BLAST Nucleic Acids Res 2004 32 Web server issue W414-W419 10.1093/ nar/gkh350 15215421 441488
22. Garg A Bhasin M Raghava GP Support Vector Machine-based method for subcellular localization of human proteins using amino acid compositions, their order, and similarity search J Biol Chem 2005, 280(15):14427-14432 10.1074/jbc.M411789200 15647269