PSI: A Comprehensive and Integrative Approach for Accurate Plant Subcellular Localization Prediction

PLoS ONE

Volumn 8, Issue 10, 2013, Pages

  Liu, Lili ^a   Zhang, Zijun ^a   Mei, Qian ^a   Chen, Ming ^a  

^a ZHEJIANG UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ACCURACY; ARTICLE; ARTIFICIAL NEURAL NETWORK; CELLULAR DISTRIBUTION; COMMUNITY INTEGRATION; COMPUTER PREDICTION; CONTROLLED STUDY; DECISION MAKING; INTEGRATIVE MEDICINE; MACHINE LEARNING; NONHUMAN; PLANT; PROTEIN ENGINEERING; PROTEIN LOCALIZATION; WEB BROWSER; COMPUTER PROGRAM; INTERNET; INTRACELLULAR SPACE; METABOLISM;

VEGETABLE PROTEIN;

INTERNET; INTRACELLULAR SPACE; PLANT PROTEINS; PLANTS; SOFTWARE;

EID: 84886035395     PISSN: None     EISSN: 19326203     Source Type: Journal    
DOI: 10.1371/journal.pone.0075826     Document Type: Article

References (33)

1. Ehrlich JS, Hansen MD, Nelson WJ, (2002) Spatio-temporal regulation of Rac1 localization and lamellipodia dynamics during epithelial cell-cell adhesion. Dev Cell 3: 259-270.
2. Glory E, Murphy RF, (2007) Automated subcellular location determination and high-throughput microscopy. Dev Cell 12: 7-16.
3. Donnes P, Hoglund A, (2004) Predicting protein subcellular localization: past, present, and future. Genomics Proteomics Bioinformatics 2: 209-215.
4. Yu CS, Lin CJ, Hwang JK, (2004) Predicting subcellular localization of proteins for Gram-negative bacteria by support vector machines based on n-peptide compositions. Protein Sci 13: 1402-1406.s.
5. Brady S, Shatkay H, (2008) EpiLoc: a (working) text-based system for predicting protein subcellular location. Pac Symp Biocomput pp. 604-615.
6. Chou KC, Shen HB, (2010) Plant-mPLoc: a top-down strategy to augment the power for predicting plant protein subcellular localization. PLoS One 5: e11335.
7. Small I, Peeters N, Legeai F, Lurin C, (2004) Predotar: A tool for rapidly screening proteomes for N-terminal targeting sequences. Proteomics 4: 1581-1590.
8. Emanuelsson O, Nielsen H, Brunak S, von Heijne G, (2000) Predicting subcellular localization of proteins based on their N-terminal amino acid sequence. J Mol Biol 300: 1005-1016.
9. Horton P, Park KJ, Obayashi T, Fujita N, Harada H, et al. (2007) WoLF PSORT: protein localization predictor. Nucleic Acids Res 35: W585-587.
10. Niu B, Jin YH, Feng KY, Lu WC, Cai YD, et al. (2008) Using AdaBoost for the prediction of subcellular location of prokaryotic and eukaryotic proteins. Mol Divers 12: 41-45.
11. Laurila K, Vihinen M, (2011) PROlocalizer: integrated web service for protein subcellular localization prediction. Amino Acids 40: 975-980.
12. Boden M, Hawkins J, (2005) Prediction of subcellular localization using sequence-biased recurrent networks. Bioinformatics 21: 2279-2286.
13. Shen YQ, Burger G, (2010) TESTLoc: protein subcellular localization prediction from EST data. BMC Bioinformatics 11: 563.
14. Chen H, Huang N, Sun Z, (2006) SubLoc: a server/client suite for protein subcellular location based on SOAP. Bioinformatics 22: 376-377.
15. Bau D, Martin AJ, Mooney C, Vullo A, Walsh I, et al. (2006) Distill: a suite of web servers for the prediction of one-, two- and three-dimensional structural features of proteins. BMC Bioinformatics 7: 402.
16. Lin HN, Chen CT, Sung TY, Ho SY, Hsu WL, (2009) Protein subcellular localization prediction of eukaryotes using a knowledge-based approach. BMC Bioinformatics 10 Suppl 15: S8.
17. Pierleoni A, Martelli PL, Fariselli P, Casadio R, (2006) BaCelLo: a balanced subcellular localization predictor. Bioinformatics 22: e408-416.
18. Guda C, (2006) pTARGET: a web server for predicting protein subcellular localization. Nucleic Acids Res 34: W210-213.
19. Guda C, Guda P, Fahy E, Subramaniam S, (2004) MITOPRED: a web server for the prediction of mitochondrial proteins. Nucleic Acids Res 32: W372-374.
20. Petsalaki EI, Bagos PG, Litou ZI, Hamodrakas SJ, (2006) PredSL: a tool for the N-terminal sequence-based prediction of protein subcellular localization. Genomics Proteomics Bioinformatics 4: 48-55.
21. Scott MS, Thomas DY, Hallett MT, (2004) Predicting subcellular localization via protein motif co-occurrence. Genome Res 14: 1957-1966.
22. Huang WL, Tung CW, Ho SW, Hwang SF, Ho SY, (2008) ProLoc-GO: utilizing informative Gene Ontology terms for sequence-based prediction of protein subcellular localization. BMC Bioinformatics 9: 80.
23. Fyshe A, Liu Y, Szafron D, Greiner R, Lu P, (2008) Improving subcellular localization prediction using text classification and the gene ontology. Bioinformatics 24: 2512-2517.
24. Claros MG, (1995) MitoProt, a Macintosh application for studying mitochondrial proteins. Comput Appl Biosci 11: 441-447.
25. Szafron D, Lu P, Greiner R, Wishart DS, Poulin B, et al. (2004) Proteome Analyst: custom predictions with explanations in a web-based tool for high-throughput proteome annotations. Nucleic Acids Res 32: W365-371.
26. Bhasin M, Raghava GP, (2004) ESLpred: SVM-based method for subcellular localization of eukaryotic proteins using dipeptide composition and PSI-BLAST. Nucleic Acids Res 32: W414-419.
27. Hoglund A, Donnes P, Blum T, Adolph HW, Kohlbacher O, (2006) MultiLoc: prediction of protein subcellular localization using N-terminal targeting sequences, sequence motifs and amino acid composition. Bioinformatics 22: 1158-1165.
28. Marbach D, Costello JC, Kuffner R, Vega NM, Prill RJ, et al. (2012) Wisdom of crowds for robust gene network inference. Nat Methods 9: 796-804.
29. Shen YQ, Burger G, (2007) 'Unite and conquer': enhanced prediction of protein subcellular localization by integrating multiple specialized tools. BMC Bioinformatics 8: 420.
30. Tanz SK, Castleden I, Hooper CM, Vacher M, Small I, et al. (2013) SUBA3: a database for integrating experimentation and prediction to define the SUBcellular location of proteins in Arabidopsis. Nucleic Acids Res 41: D1185-1191.
31. Sun Q, Zybailov B, Majeran W, Friso G, Olinares PD, et al. (2009) PPDB, the Plant Proteomics Database at Cornell. Nucleic Acids Res 37: D969-974.
32. Prill RJ, Marbach D, Saez-Rodriguez J, Sorger PK, Alexopoulos LG, et al. (2010) Towards a rigorous assessment of systems biology models: the DREAM3 challenges. PLoS One 5: e9202.
33. Carugo O, (2007) Detailed estimation of bioinformatics prediction reliability through the Fragmented Prediction Performance Plots. BMC Bioinformatics 8: 380.