BLProt: Prediction of bioluminescent proteins based on support vector machine and relieff feature selection

BMC Bioinformatics

Volumn 12, Issue , 2011, Pages

  Kandaswamy, Krishna K ^a   Pugalenthi, Ganesan ^b   Hazrati, Mehrnaz K ^a   Kalies, Kai Uwe ^a   Martinetz, Thomas ^a  

^a UNIVERSITY OF LÜBECK   (Germany)

^b KING ABDULLAH UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Saudi Arabia)

Author keywords

[No Author keywords available]

Indexed keywords

BIOTECHNOLOGICAL APPLICATIONS; HYPOTHETICAL PROTEIN; PHYSICOCHEMICAL PROPERTY; PREDICTION ACCURACY; PROMINENT FEATURES; SEQUENCE INFORMATIONS; SEQUENCE SIMILARITY; TECHNOLOGICAL ADVANCES;

BIOLOGY; FORECASTING; PHOSPHORESCENCE; PROTEINS; SUPPORT VECTOR MACHINES;

BIOLUMINESCENCE;

FUNGI; HEXAPODA;

PHOTOPROTEIN;

ANIMAL; ARTICLE; CHEMISTRY; COMPUTER PROGRAM; HUMAN; PROBABILITY; SUPPORT VECTOR MACHINE;

ANIMALS; HUMANS; LUMINESCENT PROTEINS; MARKOV CHAINS; SOFTWARE; SUPPORT VECTOR MACHINES;

EID: 80051652060     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-12-345     Document Type: Article

References (41)

1. Wilson T. Comments on the mechanisms of chemi- and bioluminescence. Photochem Photobiol 1995, 62:601-606.
2. Hastings JW. Bioluminescence 1995, Academic Press; New York.
3. Haddock SHD, Moline MA, Case JF. Bioluminescence in the Sea. Ann Rev Mar Sci 2010, 2:293-343.
4. Lloyd JE. Insect Bioluminescence 1978, Academic Press; New York.
5. White EH, Rapaport E, Seliger HH, Hopkins TA. The chemi- and bioluminescence of firefly luciferin: an efficient chemical production of electronically excited states. Bioorg Chem 1971, 1:92-122.
6. Wilson T, Hastings JW. Bioluminescence. Annual Review of Cell and Developmental Biology 1998, 14:197-230. 10.1146/annurev.cellbio.14.1.197, 9891783.
7. Cormier MJ, Lee J, Wampler JE. Bioluminescence: Recent Advances. Annual Review of Biochemistry 1975, 44:255-272. 10.1146/annurev.bi.44.070175.001351, 237461.
8. Ward WW, Swiatek GC, Gonzalez DG. Green fluorescent protein in biotechnology education. Methods Enzymol 2000, 305:672-680.
9. Chalfie M, Tu Y, Euskirchen G, Ward WW, Prasher DC. Green fluorescent protein as a marker for gene expression. Science 1994, 263:802-805. 10.1126/science.8303295, 8303295.
10. Contag CH, Bachmann MH. Advances in in vivo bioluminescence imaging of gene expression. Annu Rev Biomed Eng 2002, 4:235-260. 10.1146/annurev.bioeng.4.111901.093336, 12117758.
11. Gonzalez JE, Negulescu PA. Intracellular detection assays for high-throughput screening. Curr Opin Biotechnol 1998, 9:624-631. 10.1016/S0958-1669(98)80141-9, 9889144.
12. Kain SR. Green fluorescent protein (GFP): applications in cell-based assays for drug discovery. Drug Discov Today 1999, 4(7):304-312. 10.1016/S1359-6446(99)01330-6, 10377508.
13. DiPilato LM, Cheng X, Zhang J. Fluorescent indicators of cAMP and Epac activation reveal differential dynamics of cAMP signaling within discrete subcellular compartments. Proc Natl Acad Sci USA 2004, 101:16513-16518. 10.1073/pnas.0405973101, 534508, 15545605.
14. Hayes MJ, Merrifield CJ, Shao D, Ayala-Sanmartin J, Schorey CD, Levine TP, Proust J, Curran J, Bailly M, Moss SE. Annexin 2 Binding to Phosphatidylinositol 4, 5-Bisphosphate on Endocytic Vesicles Is Regulated by the Stress Response Pathway. J Biol Chem 2004, 279:14157-14164. 10.1074/jbc.M313025200, 1351152, 14734570.
15. Sanger F, Nicklen S, Coulson AR. DNA sequencing with chain-terminating inhibitors. Proc Natl Acad Sci USA 1977, 74:5463-5467. 10.1073/pnas.74.12.5463, 431765, 271968.
16. Zhang ZH, Wang ZH, Zhang ZR, Wang YX. A novel method for apoptosis protein subcellular localization prediction combining encoding based on grouped weight and support vector machine. FEBS Lett 2006, 580:6169-6174. 10.1016/j.febslet.2006.10.017, 17069811.
17. Zhou XB, Chen C, Li ZC, Zou XY. Using Chou's amphiphilic pseudo- amino acid composition and support vector machine for prediction of enzyme subfamily classes. J Theor Biol 2007, 248:546-551. 10.1016/j.jtbi.2007.06.001, 17628605.
18. Brown MP, Grundy WN, Lin D, Cristianini N, Sugnet CW, Furey TS, Ares M, Haussler D. Knowledge-based analysis of microarray gene expression data using SVM. Proceedings of the National Academy of Sciences 97(1):262-267.
19. Altschul SF, Madden TL, Schaffer AA, Zhang J, Zhang Z, Miller W, Lipman DJ. Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucleic Acids Res 1997, 25(17):3389-3402. 10.1093/nar/25.17.3389, 146917, 9254694.
20. Eddy SR. Profile hidden Markov models. Bioinformatics 1998, 14(9):755-763. 10.1093/bioinformatics/14.9.755, 9918945.
21. Sonnhammer EL, Eddy SR, Durbin R. Pfam: a comprehensive database of protein domain families based on seed alignments. Proteins 1997, 28(3):405-420. 10.1002/(SICI)1097-0134(199707)28:3<405::AID-PROT10>3.0.CO;2-L, 9223186.
22. Hunter S, Apweiler R, Attwood TK, Bairoch A, Bateman A, Binns D, Bork P, Das U, Daugherty L, Duquenne L, Finn RD, Gough J, Haft D, Hulo N, Kahn D, Kelly E, Laugraud A, Letunic I, Lonsdale D, Lopez R, Madera M, Maslen J, McAnulla C, McDowall J, Mistry J, Mitchell A, Mulder N, Natale D, Orengo C, Quinn AF, et al. InterPro: the integrative protein signature database. Nucleic Acids Res 2009, (37 Database):D224-D228.
23. Marchler-Bauer A, Lu S, Anderson JB, Chitsaz F, Derbyshire MK, DeWeese-Scott C, Fong JH, Geer LY, Geer RC, Gonzales NR, Gwadz M, Hurwitz DI, Jackson JD, Ke Z, Lanczycki CJ, Lu F, Marchler GH, Mullokandov M, Omelchenko MV, Robertson CL, Song JS, Thanki N, Yamashita RA, Zhang D, Zhang N, Zheng C, Bryant SH. CDD: a Conserved Domain Database for the functional annotation of proteins. Nucleic Acids Res 2011, (39 Database):D225-9.
24. Kanehisa M, Goto S. KEGG: Kyoto encyclopedia of genes and genomes. Nucleic Acids Res 2000, 28:27-30. 10.1093/nar/28.1.27, 102409, 10592173.
25. Quinlan R. C4.5. Programs for Machine Learning 1993, Morgan Kaufmann Publishers; San Mateo; CA.
26. Frank E, Witten IH. Generating Accurate Rule Sets Without Global Optimization. Fifteenth International Conference on Machine Learning 1998, 144-151.
27. Breiman L. Random Forests. Machine Learning 2001, 45:5-32.
28. Freund Y, Schapire RE. Experiments with a new boosting algorithm. Thirteenth International Conference on Machine Learning, San Francisco 1996, 148-156.
29. Aha D, Kibler D. Instance-based learning algorithms. Machine Learning 1991, 6:37-66.
30. Li W, Jaroszewski L, Odzik GA. Clustering of highly homologous sequences to reduce the size of large protein database. Bioinformatics 2001, 17:282-283. 10.1093/bioinformatics/17.3.282, 11294794.
31. Kawashima S, Ogata H, Kanehisa M. AAindex: amino acid index database. Nucleic Acids Res 1999, 27:368-369. 10.1093/nar/27.1.368, 148186, 9847231.
32. Pugalenthi G, Kumar KK, Suganthan PN, Gangal R. Identification of catalytic residues from protein structure using support vector machine with sequence and structural features. Biochem Biophys Res Commun 2008, 367:630-634. 10.1016/j.bbrc.2008.01.038, 18206645.
33. Cai YD, Pong-Wong R, Feng K, Jen JCH, Chou KC. Application of SVM to predict membrane protein types. Journal of Theoretical Biology 2004, 226:373-376. 10.1016/j.jtbi.2003.08.015, 14759643.
34. Cai YD, Liu XJ, Xu XB, Chou KC. Prediction of protein structural classes by support vector machines. Computers & Chemistry 2002, 26:293-296.
35. Vapnik V. Statistical Learning Theory 1998, Wiley-Interscience; New York.
36. Muller KR, Mika S, Ratsch K, Tsuda K, Scholkopf B. An introduction to kernel-based learning algorithms. IEEE Trans Neural Networks 2001, 2:181-201.
37. Chang CC, Lin CJ. LIBSVM: A Library for Support Vector Machines. 2001, , http://www.csie.ntu.edu.tw/~cjlin/libsvm
38. Joachims T. Optimizing Search Engines Using Clickthrough Data. Proceedings of the ACM Conference on Knowledge Discovery and Data Mining (KDD), ACM 2002,
39. Haindl M, Somol P, Ververidis D, Kotropoulos C. Feature Selection Based on Mutual Correlation. Progress in Pattern Recognition, Image Anal Appl 2006, 4225:569-577.
40. Zhang Y, Ding C, Li T. Gene selection algorithm by combining reliefF and mRMR. BMC Genomics 2008, 9:S27. 10.1186/1471-2164-9-S2-S27, 2559892, 18831793.
41. Peng HC, Long F, Ding C. Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy. IEEE Transactions on Pattern Analysis and Machine Intelligence 2005, 27(8):1226-1238.