Predicting Gram-positive bacterial protein subcellular localization based on localization motifs

Journal of Theoretical Biology

Volumn 308, Issue , 2012, Pages 135-140

  Hu, Yinxia ^a   Li, Tonghua ^a   Sun, Jiangming ^a   Tang, Shengnan ^a   Xiong, Wenwei ^a   Li, Dapeng ^a   Chen, Guanyan ^a   Cong, Peisheng ^a  

^a TONGJI UNIVERSITY   (China)

Author keywords

Motif finding; Position specific frequencies encoding; Subcellular location prediction; Support vector machine (SVM)

Indexed keywords

BACTERIAL PROTEIN;

BACTERIUM; CELL ORGANELLE; PROTEIN;

ACCURACY; ARTICLE; CELLULAR DISTRIBUTION; GRAM POSITIVE BACTERIUM; NONHUMAN; PRIORITY JOURNAL; PROTEIN FUNCTION; PROTEIN LOCALIZATION; PROTEIN MOTIF; VALIDATION PROCESS;

AMINO ACID MOTIFS; AMINO ACID SEQUENCE; BACTERIAL PROTEINS; DATABASES, PROTEIN; GRAM-POSITIVE BACTERIA; MODELS, BIOLOGICAL; MOLECULAR SEQUENCE DATA; PROTEIN TRANSPORT; REPRODUCIBILITY OF RESULTS; SUBCELLULAR FRACTIONS;

BACTERIA (MICROORGANISMS); POSIBACTERIA;

EID: 84862677130     PISSN: 00225193     EISSN: 10958541     Source Type: Journal    
DOI: 10.1016/j.jtbi.2012.05.031     Document Type: Article

References (39)

1. Bhasin M., Raghava G.P. ESLpred: SVM-based method for subcellular localization of eukaryotic proteins using dipeptide composition and PSI-BLAST. Nucleic Acids Res. 2004, 32:W414-9.
2. Bryant D.M., Stow J.L. The ins and outs of E-cadherin trafficking. Trends Cell Biol. 2004, 14:427-434.
3. Chou K.C. Structural bioinformatics and its impact to biomedical science. Curr. Med. Chem. 2004, 11:2105-2134.
4. Chou K.C. Some remarks on protein attribute prediction and pseudo amino acid composition. J. Theor. Biol. 2011, 273:236-247.
5. Chou K.C., Cai Y.D. Using functional domain composition and support vector machines for prediction of protein subcellular location. J. Biol. Chem. 2002, 277:45765-45769.
6. Chou K.C., Shen H.B. Cell-PLoc: a package of web servers for predicting subcellular localization of proteins in various organisms. Nat. Protoc. 2008, 3:153-162.
7. Chou K.C., Shen H.B. Review: recent advances in developing web-servers for predicting protein attributes. Nat. Sci. 2009, 2:63-92.
8. Chou K.C., Wu Z.C., Xiao X. iLoc-Hum: using the accumulation-label scale to predict subcellular locations of human proteins with both single and multiple sites. Mol. Biosyst. 2012, 8:629-641.
9. Emanuelsson O., Nielsen H., Brunak S., von Heijne G. Predicting subcellular localization of proteins based on their N-terminal amino acid sequence. J. Mol. Biol. 2000, 300:1005-1016.
10. Gao Q.B., Wang Z.Z., Yan C., Du Y.H. Prediction of protein subcellular location using a combined feature of sequence. FEBS Lett. 2005, 579:3444-3448.
11. Huang J., Li T., Chen K., Wu J. An approach of encoding for prediction of splice sites using SVM. Biochimie 2006, 88:923-929.
12. Lubec G., Afjehi-Sadat L., Yang J.W., John J.P. Searching for hypothetical proteins: theory and practice based upon original data and literature. Program Neurobiol. 2005, 77:90-127.
13. Martin G.S., Mannino D.M., Eaton S., Moss M. The epidemiology of sepsis in the United States from 1979 through 2000. N. Engl. J. Med. 2003, 348:1546-1554.
14. Nakai K. Protein sorting signals and prediction of subcellular localization. Adv. Protein Chem. 2000, 54:277-344.
15. Nakai K. Protein sorting signals and prediction of subcellular localization. Adv. Protein Chem. 2000, 54:277-344.
16. Nakai K., Horton P. PSORT: a program for detecting sorting signals in proteins and predicting their subcellular localization. Trends Biochem. Sci. 1999, 24:34-36.
17. Nakai K., Kanehisa M. Expert system for predicting protein localization sites in Gram-negative bacteria. Proteins 1991, 11:95-110.
18. Rashid M., Saha S., Raghava G.P. Support vector machine-based method for predicting subcellular localization of mycobacterial proteins using evolutionary information and motifs. BMC Bioinf. 2007, 8:337.
19. Reinhardt A., Hubbard T. Using neural networks for prediction of the subcellular location of proteins. Nucleic Acids Res. 1998, 26:2230-2236.
20. Restrepo-Montoya D., Pino C., Nino L.F., Patarroyo M.E., Patarroyo M.A. NClassG+: a classifier for non-classically secreted Gram-positive bacterial proteins. BMC Bioinf. 2011, 12:21.
21. Rolston K.V. Challenges in the treatment of infections caused by Gram-positive and Gram-negative bacteria in patients with cancer and neutropenia. Clin. Infect. Dis. 2005, 40(Suppl 4):S246-S252.
22. Shen H.B., Chou K.C. Gpos-PLoc: an ensemble classifier for predicting subcellular localization of Gram-positive bacterial proteins. Protein Eng. Des. Sel. 2007, 20:39-46.
23. Shen H.B., Chou K.C. Gpos-mPLoc: a top-down approach to improve the quality of predicting subcellular localization of Gram-positive bacterial proteins. Protein Pept. Lett. 2009, 16:1478-1484.
24. Shen H.B., Chou K.C. Gneg-mPLoc: a top-down strategy to enhance the quality of predicting subcellular localization of Gram-negative bacterial proteins. J. Theor. Biol. 2010, 264:326-333.
25. Shurety W., Merino-Trigo A., Brown D., Hume D.A., Stow J.L. Localization and post-golgi trafficking of tumor necrosis factor-alpha in macrophages. J. Interferon Cytokine Res. 2000, 20:427-438.
26. Tang S.N., Sun J.M., Xiong W.W., Cong P.S., Li T.H. Identification of the subcellular localization of mycobacterial proteins using localization motifs. Biochimie 2012, 94:847-853.
27. Wang X., Meng X., Kuhlman J.R., Nelin L.D., Nicol K.K., English B.K., Liu Y. Knockout of Mkp-1 enhances the host inflammatory responses to Gram-positive bacteria. J. Immunol. 2007, 178:5312-5320.
28. Weber J.R., Moreillon P., Tuomanen E.I. Innate sensors for Gram-positive bacteria. Curr. Opin. Immunol. 2003, 15:408-415.
29. Wisplinghoff H., Seifert H., Wenzel R.P., Edmond M.B. Current trends in the epidemiology of nosocomial bloodstream infections in patients with hematological malignancies and solid neoplasms in hospitals in the United States. Clin. Infect. Dis. 2003, 36:1103-1110.
30. Xiao X., Wu Z.C., Chou K.C. A multi-label classifier for predicting the subcellular localization of Gram-negative bacterial proteins with both single and multiple sites. PLoS One 2011, 6:e20592.
31. Xiao X., Wu Z.C., Chou K.C. iLoc-Virus: a multi-label learning classifier for identifying the subcellular localization of virus proteins with both single and multiple sites. J. Theor. Biol. 2011, 284:42-51.
32. Xiong W., Li T., Chen K., Tang K. Local combinational variables: an approach used in DNA-binding helix-turn-helix motif prediction with sequence information. Nucleic Acids Res. 2009, 37:5632-5640.
33. Yadegarynia D., Tarrand J., Raad I., Rolston K. Current spectrum of bacterial infections in patients with cancer. Clin. Infect. Dis. 2003, 37:1144-1145.
34. Yu C.S., Lin C.J., Hwang J.K. Predicting subcellular localization of proteins for Gram-negative bacteria by support vector machines based on n-peptide compositions. Protein Sci. 2004, 13:1402-1406.
35. Yu C.S., Chen Y.C., Lu C.H., Hwang J.K. Prediction of protein subcellular localization. Proteins 2006, 64:643-651.
36. Yu N.Y., Wagner J.R., Laird M.R., Melli G., Rey S., Lo R., Dao P., Sahinalp S.C., Ester M., Foster L.J., Brinkman F.S. PSORTb 3.0: improved protein subcellular localization prediction with refined localization subcategories and predictive capabilities for all prokaryotes. Bioinformatics 2010, 26:1608-1615.
37. Yuan Z. Prediction of protein subcellular locations using Markov chain models. FEBS Lett. 1999, 451:23-26.
38. Zhang L., Liao B., Li D., Zhu W. A novel representation for apoptosis protein subcellular localization prediction using support vector machine. J. Theor. Biol. 2009, 259:361-365.
39. Zinner S.H. Changing epidemiology of infections in patients with neutropenia and cancer: emphasis on Gram-positive and resistant bacteria. Clin. Infect. Dis. 1999, 29:490-494.