Protein subcellular localization prediction of eukaryotes using a knowledge-based approach

BMC Bioinformatics

Volumn 10, Issue SUPPL. 15, 2009, Pages

  Lin, Hsin Nan ^a,b,c   Chen, Ching Tai ^a,b,c   Sung, Ting Yi ^b   Ho, Shinn Ying ^c   Hsu, Wen Lian ^b  

^a ACADEMIA SINICA   (Taiwan)

^b INSTITUTE OF INFORMATION SCIENCE   (Taiwan)

^c NATIONAL CHIAO TUNG UNIVERSITY   (Taiwan)

Author keywords

[No Author keywords available]

Indexed keywords

FORECASTING; KNOWLEDGE BASED SYSTEMS; BIOINFORMATICS; DATA PROCESSING; PROTEINS;

CELLULAR COMPARTMENTS; COMPUTATIONAL APPROACH; KNOWLEDGE-BASED APPROACH; KNOWLEDGE-BASED METHODS; PROTEIN SUBCELLULAR LOCALIZATION; PROTEIN SUBCELLULAR LOCALIZATION PREDICTION; SEQUENCE SIMILARITY; SUBCELLULAR ORGANELLES; ACCURATE PREDICTION; BIOLOGICAL PROCESS; CELLULAR PROCESS; CROSS VALIDATION; DATA SETS; EUKARYOTIC PROTEINS; KNOWLEDGE BASE; LOCAL SIMILARITY; PREDICTION ACCURACY; PREDICTION PROCESS; PREDICTION SYSTEMS; PROTEIN FUNCTIONS; PROTEIN SEQUENCES; QUERY PROTEINS; SEQUENCE VARIATIONS;

PROTEINS; EXPERIMENTS;

ACCURACY; AMINO ACID SEQUENCE; ARTICLE; CELL ORGANELLE; CELLULAR DISTRIBUTION; EUKARYOTE; INFORMATION PROCESSING; KNOWLEDGE; METHODOLOGY; NONHUMAN; PERFORMANCE; PREDICTION; PROTEIN LOCALIZATION; BIOLOGY; CHEMISTRY; COMPUTER PROGRAM; KNOWLEDGE BASE; PROTEIN DATABASE; SEQUENCE ANALYSIS;

EUKARYOTA;

PROTEIN;

COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; EUKARYOTA; KNOWLEDGE BASES; PROTEINS; SEQUENCE ANALYSIS, PROTEIN; SOFTWARE;

EID: 71549120704     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-10-S15-S8     Document Type: Article

References (32)

1. Nair R, Rost B. Better prediction of sub-cellular localization by combining evolutionary and structural information. Proteins 2003, 53(4):917-930. 10.1002/prot.10507, 14635133.
2. Gardy JL, Laird MR, Chen F, Rey S, Walsh CJ, Ester M, Brinkman FS. PSORTb v.2.0: expanded prediction of bacterial protein subcellular localization and insights gained from comparative proteome analysis. Bioinformatics 2005, 21(5):617-623. 10.1093/bioinformatics/bti057, 15501914.
3. Hoglund A, Donnes P, Blum T, Adolph HW, Kohlbacher O. MultiLoc: prediction of protein subcellular localization using N-terminal targeting sequences, sequence motifs and amino acid composition. Bioinformatics 2006, 22(10):1158-1165. 10.1093/bioinformatics/btl002, 16428265.
4. Wang JR, Sung WK, Krishnan A, Li KB. Protein subcellular localization prediction for Gram-negative bacteria using amino acid subalphabets and a combination of multiple support vector machines. BMC Bioinformatics 2005, 6:174. 1190155, 16011808, 10.1186/1471-2105-6-174.
5. Yu CS, Chen YC, Lu CH, Hwang JK. Prediction of protein subcellular localization. Proteins 2006, 64(3):643-651. 10.1002/prot.21018, 16752418.
6. Yu CS, Lin CJ, Hwang JK. Predicting subcellular localization of proteins for Gram-negative bacteria by support vector machines based on n-peptide compositions. Protein Sci 2004, 13(5):1402-1406. 10.1110/ps.03479604, 2286765, 15096640.
7. Chang JM, Su EC, Lo A, Chiu HS, Sung TY, Hsu WL. PSLDoc: Protein subcellular localization prediction based on gapped-dipeptides and probabilistic latent semantic analysis. Proteins 2008, 72(2):693-710. 10.1002/prot.21944, 18260102.
8. Bhasin M, Garg A, Raghava GP. PSLpred: prediction of subcellular localization of bacterial proteins. Bioinformatics 2005, 21(10):2522-2524. 10.1093/bioinformatics/bti309, 15699023.
9. Chou KC, Cai YD. Predicting protein localization in budding yeast. Bioinformatics 2005, 21(7):944-950. 10.1093/bioinformatics/bti104, 15513989.
10. Gardy JL, Spencer C, Wang K, Ester M, Tusnady GE, Simon I, Hua S, deFays K, Lambert C, Nakai K. PSORT-B: Improving protein subcellular localization prediction for Gram-negative bacteria. Nucleic Acids Res 2003, 31(13):3613-3617. 10.1093/nar/gkg602, 169008, 12824378.
11. Lee K, Kim DW, Na D, Lee KH, Lee D. PLPD: reliable protein localization prediction from imbalanced and overlapped datasets. Nucleic Acids Res 2006, 34(17):4655-4666. 10.1093/nar/gkl638, 1636404, 16966337.
12. Nair R, Rost B. Mimicking cellular sorting improves prediction of subcellular localization. J Mol Biol 2005, 348(1):85-100. 10.1016/j.jmb.2005.02.025, 15808855.
13. Huang WL, Tung CW, Ho SW, Hwang SF, Ho SY. ProLoc-GO: utilizing informative Gene Ontology terms for sequence-based prediction of protein subcellular localization. BMC Bioinformatics 2008, 9:80. 10.1186/1471-2105-9-80, 2262056, 18241343.
14. Marcotte EM, Xenarios I, Bliek AM, Eisenberg D. Localizing proteins in the cell from their phylogenetic profiles. Proc Natl Acad Sci USA 2000, 97(22):12115-12120. 10.1073/pnas.220399497, 17303, 11035803.
15. Mott R, Schultz J, Bork P, Ponting CP. Predicting protein cellular localization using a domain projection method. Genome Res 2002, 12(8):1168-1174. 10.1101/gr.96802, 186639, 12176924.
16. Su EC, Chiu HS, Lo A, Hwang JK, Sung TY, Hsu WL. Protein subcellular localization prediction based on compartment-specific features and structure conservation. BMC Bioinformatics 2007, 8:330. 10.1186/1471-2105-8-330, 2040162, 17825110.
17. Rychlewski L, Jaroszewski L, Li WZ, Godzik A. Comparison of sequence profiles. Strategies for structural predictions using sequence information. Protein Science 2000, 9(2):232-241. 2144550, 10716175.
18. Sadreyev R, Grishin N. COMPASS: A tool for comparison of multiple protein alignments with assessment of statistical significance. Journal of Molecular Biology 2003, 326(1):317-336. 10.1016/S0022-2836(02)01371-2, 12547212.
19. Przybylski D, Rost B. Consensus sequences improve PSI-BLAST through mimicking profile-profile alignments. Nucleic Acids Research 2007, 35(7):2238-2246. 10.1093/nar/gkm107, 1874647, 17369271.
20. Pietrokovski S. Searching databases of conserved sequence regions by aligning protein multiple-alignments. Nucleic Acids Research 1996, 24(19):3836-3845. 10.1093/nar/24.19.3836, 146152, 8871566.
21. Yona G, Levitt M. Within the twilight zone: A sensitive profile-profile comparison tool based on information theory. Journal of Molecular Biology 2002, 315(5):1257-1275. 10.1006/jmbi.2001.5293, 11827492.
22. Zhang S, Xia X, Shen J, Zhou Y, Sun Z. DBMLoc: a Database of proteins with multiple subcellular localizations. BMC Bioinformatics 2008, 9:127. 10.1186/1471-2105-9-127, 2292141, 18304364.
23. King BR, Guda C. ngLOC: an n-gram-based Bayesian method for estimating the subcellular proteomes of eukaryotes. Genome Biology 2007, 8(5). 10.1186/gb-2007-8-5-r68, 1929137, 17472741.
24. Lin HN, Chang JM, Wu KP, Sung TY, Hsu WL. HYPROSP II--a knowledge-based hybrid method for protein secondary structure prediction based on local prediction confidence. Bioinformatics 2005, 21(15):3227-3233. 10.1093/bioinformatics/bti524, 15932901.
25. Wu KP, Lin HN, Chang JM, Sung TY, Hsu WL. HYPROSP: a hybrid protein secondary structure prediction algorithm--a knowledge-based approach. Nucleic Acids Res 2004, 32(17):5059-5065. 10.1093/nar/gkh836, 521652, 15448186.
26. Chen CT, Lin HN, Sung TY, Hsu WL. HYPLOSP: a knowledge-based approach to protein local structure prediction. J Bioinform Comput Biol 2006, 4(6):1287-1307. 10.1142/S0219720006002466, 17245815.
27. Bolten E, Schliep A, Schneckener S, Schomburg D, Schrader R. Clustering protein sequences-structure prediction by transitive homology. Bioinformatics 2001, 17(10):935-941. 10.1093/bioinformatics/17.10.935, 11673238.
28. Jones DT, Swindells MB. Getting the most from PSI-BLAST. Trends in Biochemical Sciences 2002, 27(3):161-164. 10.1016/S0968-0004(01)02039-4, 11893514.
29. Forslund K, Sonnhammer ELL. Predicting protein function from domain content. Bioinformatics 2008, 24(15):1681-1687. 10.1093/bioinformatics/btn312, 18591194.
30. Nakai K, Horton P. PSORT: a program for detecting sorting signals in proteins and predicting their subcellular localization. Trends Biochem Sci 1999, 24(1):34-36. 10.1016/S0968-0004(98)01336-X, 10087920.
31. Guda C, Subramaniam S. pTARGET: a new method for predicting protein subcellular localization in eukaryotes. Bioinformatics 2005, 21(24):4434-4434. 10.1093/bioinformatics/bti758.
32. 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. 10.1093/bioinformatics/btg222, 12967962.