Protein sequences classification by means of feature extraction with substitution matrices

BMC Bioinformatics

Volumn 11, Issue , 2010, Pages

  Saidi, Rabie ^a,b,c,d   Maddouri, Mondher ^d,e   Mephu Nguifo, Engelbert ^a,b  

^a UNIVERSITÉ CLERMONT AUVERGNE   (France)

^b CNRS   (France)

^c UNIVERSITY OF JENDOUBA   (Tunisia)

^d FACULTÉ DES SCIENCES DE TUNIS   (Tunisia)

^e UNIVERSITY OF GAFSA   (Tunisia)

Author keywords

[No Author keywords available]

Indexed keywords

BIOLOGICAL SEQUENCES; CLASSIFICATION ACCURACY; CLASSIFICATION QUALITY; CLASSIFICATION TASKS; COMPARATIVE EXPERIMENTS; LEARNING CLASSIFIERS; PROTEIN CLASSIFICATION; SUPERVISED CLASSIFICATION;

ENCODING (SYMBOLS); EXTRACTION; FEATURE EXTRACTION; LEARNING SYSTEMS; PROTEINS;

CLASSIFICATION (OF INFORMATION);

PROTEIN;

AMINO ACID SEQUENCE; AMINO ACID SUBSTITUTION; ARTICLE; ARTIFICIAL INTELLIGENCE; CLASSIFICATION; GENETICS; MOLECULAR GENETICS; PROTEIN DATABASE; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS; SEQUENCE HOMOLOGY;

AMINO ACID SEQUENCE; AMINO ACID SUBSTITUTION; ARTIFICIAL INTELLIGENCE; DATABASES, PROTEIN; MOLECULAR SEQUENCE DATA; PROTEINS; SEQUENCE ALIGNMENT; SEQUENCE ANALYSIS, PROTEIN; SEQUENCE HOMOLOGY, AMINO ACID;

EID: 77950680873     PISSN: None     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-11-175     Document Type: Article

References (51)

1. Bhaskar H, Hoyle DC, Singh S. Machine learning in bioinformatics: A brief survey and recommendations for practitioners. Computers in Biology and Medicine 2005, 36:1104-1125. 10.1016/j.compbiomed.2005.09.002, 16226240.
2. Bernardes J, Fernandez J, Vasconcelos A. Structural descriptor database: a new tool for sequence based functional site prediction. BMC Bioinformatics 2008, 9:492. 10.1186/1471-2105-9-492, 2612011, 19032768.
3. Klotz C, Aumont MC, Leger JJ, Swynghedauw B. Human cardiac myosin ATPase and light subunits: A comparative study. Biochim Biophys 1975, 386:461-469.
4. Price NC. Assembly of multi-subunit structure. Mechanisms of Protein Folding 1994, 160-193. Oxford University Press, New York, Pain RH.
5. Corrales FJ, Fersht AR. Kinetic significance of GroEL14·(GroES7)2 complexes in molecular chaperone activity. Folding & Design 1996, 1:265-273.
6. Terry BF, Richard MC. Determination of protein-protein interactions by matrix-assisted laser desorption/ionization mass spectrometry. J Mass Spectrom 1998, 33:697-704. 10.1002/(SICI)1096-9888(199808)33:8<697::AID-JMS711>3.0.CO;2-H, 9786710.
7. Slama P, Filippis I, Lappe M. Detection of protein catalytic residues at high precision using local network properties. BMC Bioinformatics 2008, 9:517. 10.1186/1471-2105-9-517, 2632678, 19055796.
8. Mephu Nguifo E, Sallantin J. Prediction of Primate Splice Junction Gene Sequences with a Cooperative Knowledge Acquisition System. ISMB 1993, 292-300.
9. Lemoine E, Merceron D, Sallantin J, Mephu Nguifo E. Improving the Efficiency of a User-Driven Learning System with Reconfigurable Hardware. Application to DNA Splicing. Pacific Symposium on Biocomputing 1999, 290-301.
10. Vignal L, D'Aubenton-Carafa Y, Lisacek F, Mephu Nguifo E, Rouze P, Quinqueton J, Thermes C. Exon prediction in eucaryotic genomes. Biochimie 1997, 78:327-334.
11. Han J, Kamber M. Data Mining: Concepts and Techniques. 2006, Morgan Kaufmann Publishers.
12. Huan L, Motoda H. Feature Extraction, Construction and Selection: A Data Mining Perspective. ISBN: 978-0-7923-8196-9. 1998, Kluwer Academic Publishers, Norwell, MA.
13. Nevill-Manning CG, Wu TD, Brutlag DL. Highly specific protein sequence motifs for genome analysis. Proceedings of the National Academy of Sciences of the United States of America 1998, 95(11):5865-5871. 10.1073/pnas.95.11.5865, 34488, 9600885.
14. Maddouri M, Elloumi M. Encoding of primary structures of biological macromolecules within a data mining perspective. Journal of Computer Science and Technology (JCST) 2004, 19(1):78-88.
15. Yongqiang Z, Zaki MJ. EXMOTIF: efficient structured motif extraction. Journal of Algorithms for Molecular Biology 2006, 1:21.
16. Yongqiang Z, Zaki MJ. SMOTIF: efficient structured pattern and profile motif search. Journal of Algorithms for Molecular Biology 2006, 1:22.
17. Lopes F, Martins D, Cesar R. Feature selection environment for genomic applications. BMC Bioinformatics 2008, 9:451. 10.1186/1471-2105-9-451, 2655091, 18945362.
18. Saidi R, Maddouri M, Mephu Nguifo E. Biological Sequences Encoding for Supervised Classification. Intl. conf. on BioInformatics Research and Development (BIRD), TU Berlin, March 12-14, Springer-Verlag, LNBI 4414 2007, 224-238.
19. Henikoff S, Henikoff JG. Amino acid substitution matrices from protein blocks. National Academy of Sciences, USA 1992, 89:10915-10919.
20. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. Journal of Molecular Biology 1990, 215(3):403-413.
21. Leslie C, Eskin E, Noble WS. The spectrum kernel: a string kernel for svm protein classification. Pacific Symposium on Biocomputing (PSB;) 2002, 564-575.
22. Wang JTL, Marr TG, Shasha D, Shapiro BA, Chirn GW. Discovering active motifs in sets of related protein sequences and using them for classification. Nucleic Acids Research 1994, 22(14):2769-2775. 10.1093/nar/22.14.2769, 308246, 8052532.
23. Hui LCK, Crochemore M, Galil Z, Manber U. Combinatorial Pattern Matching. Lecture Notes in Computer Science in Apostolico, Springer-Verlag 1992, 644:230-243.
24. Zhang CT, Chou KC, Maggiora GM. Predicting protein structural classes from amino acid composition: Application of fuzzy clustering. Protein Eng 1995, 8:425-435. 10.1093/protein/8.5.425, 8532663.
25. Chou KC, Cai YD. Predicting protein quaternary structure by pseudo amino acid composition. Proteins 2003, 53:282-289. 10.1002/prot.10500, 14517979.
26. Zhang SW, Pan Q, Zhang HC, Zhang YL, Wang HY. Classification of protein quaternary structure with support vector machine. Bioinformatics 2003, 19:2390-2396. 10.1093/bioinformatics/btg331, 14668222.
27. Zhou GP. An intriguing controversy over protein structural class prediction. J Protein Chem 1998, 17:729-738. 10.1023/A:1020713915365, 9988519.
28. Finn RD, Tate J, Mistry J, Coggill PC, Sammut JS, Hotz HR, Ceric G, Forslund K, Eddy SR, Sonnhammer EL, Bateman A. The Pfam protein families database. Nucleic Acids Research 2008, 36:D281-D288. 10.1093/nar/gkm960, 2238907, 18039703.
29. Karp R, Miller RE, Rosenberg AL. Rapid Identification of Repeated Patterns in Strings, Trees and Arrays. 4th Symposium of Theory of Computing 1972, 125-136.
30. Malde K. The effect of sequence quality on sequence alignment. Bioinformatics 2008, 24(7):897-900. 10.1093/bioinformatics/btn052, 18296747.
31. Witten IH, Eibe F. Data Mining: Practical machine learning tools and techniques. 2005, Morgan Kaufmann, San Francisco, 2.
32. Yu X, Wang C, Li Y. Classification of protein quaternary structure by functional domain composition. BMC Bioinformatics 2006, 7:187-192. 10.1186/1471-2105-7-187, 1450311, 16584572.
33. Chou PY. Prediction of protein structural classes from amino acid composition. Prediction of Protein Structure and the Principles of Protein Conformation 1989, 549-586. Plenum Press, New York, Fasman GD.
34. Nakashima H, Nishikawa K, Ooi T. The folding type of a protein is relevant to the amino acid composition. J Biochem 1986, 99:152-162.
35. Cai YD, Liu XJ, Xu XB, Zhou GP. Support vector machines for predicting protein structural class. BMC Bioinform 2001, 2:1-5.
36. Cai YD, Zhou GP. Prediction of protein structural classes by neural network. Biochimie 2000, 82:783-785. 10.1016/S0300-9084(00)01161-5, 11018296.
37. Feng KY, Cai YD, Chou KC. Boosting classifier for predicting protein domain structural class. Biochem Biophys Res Commun 2005, 334:213-217. 10.1016/j.bbrc.2005.06.075, 15993842.
38. Cao YF, Liu S, Zhang LD, Qin J, Wang J, Tang KX. Prediction of protein structural class with Rough Sets. BMC Bioinform 2006, 7.
39. Bairoch A, Apweiler R. The SWISS-PROT protein sequence database and its supplement TrEMBL in 2000. Nucleic Acids Research 2000, 28(1):45-48. 10.1093/nar/28.1.45, 102476, 10592178.
40. Andreeva A, Howorth D, Brenner SE, Hubbard TJP, Chothia C, Murzin AG. SCOP database in 2004: refinements integrate structure and sequence family data. Nucl Acid Res 2004, 32:D226-D229.
41. Dayhoff MO, Schwartz RM, Orcutt BC. A Model of Evolutionary Change in Proteins. National Biomedical Research Foundation, Washington DC 1978, 5:345-352.
42. Zhang SW, Pan Q, Zhang HC, Shao ZC, Shi JY. Prediction protein homooligomer types by pesudo amino acid composition: approached with an improved feature extraction and Naive Bayes feature fusion. Amino Acids 2006, 30:461-468. 10.1007/s00726-006-0263-8, 16773245.
43. Song J, Tang H. Accurate classification of homodimeric vs other homooligomeric proteins using a new measure of information discrepancy. J Chem Inf Comput Sci 2004, 44:1324-1327.
44. Chou KC. Prediction of protein structural classes and subcellular locations. Curr Protein Peptide Sci 2000, 1:171-208.
45. Chou KC, Cai YD. Predicting protein structural class by functional domain composition. Biochem Biophys Res Commun 2004, 321:1007-1009. 10.1016/j.bbrc.2004.07.059, 15358128.
46. Mardia KV, Kent JT, Bibby JM. Multivariate analysis. 1979, 322-381. London: Academic Press.
47. Chen C, Zhou XB, Tian YX, Zhou XY, Cai PX. Predicting protein structural class with pseudo-amino acid composition and support vector machine fusion network. Anal Biochem 2006, 357:116-121. 10.1016/j.ab.2006.07.022, 16920060.
48. Chou KC, Zhang CT. Review: Prediction of protein structural classes. Crit Rev Biochem Mol Biol 1995, 30:275-349. 10.3109/10409239509083488, 7587280.
49. Zweig MH, Campbell G. Receiver-operating characteristic (ROC) plots: a fundamental evaluation tool in clinical medicine. Clinical chemistry 1993, 39(8):561-577.
50. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE. The Protein Data Bank. Nucleic Acids Res 2000, 28(1):235-242. 10.1093/nar/28.1.235, 102472, 10592235.
51. Sander C, Schneider R. Database of homology derived protein structure and the structural meaning of sequence alignment. Protein: Structure, Function and Genetic 1991, 9:56-68.