Prediction of protein accessible surface areas by support vector regression

Proteins: Structure, Function and Genetics

Volumn 57, Issue 3, 2004, Pages 558-564

  Yuan, Zheng ^a   Huang, Bixing ^b  

^a UNIVERSITY OF QUEENSLAND   (Australia)

^b QLD Health Scientific Services   (Australia)

Author keywords

Accessible surface area; Machine learning; Protein sequence analysis; Protein structure prediction; Solvent accessibility; Support vector

Indexed keywords

AMINO ACID; ARGININE; CYSTEINE; SOLVENT;

ANALYTICAL ERROR; ARTICLE; CLASSIFICATION; CORRELATION COEFFICIENT; PREDICTION; PRIORITY JOURNAL; PROTEIN ANALYSIS; REGRESSION ANALYSIS; SURFACE PROPERTY;

ARGININE; BINDING SITES; COMPUTATIONAL BIOLOGY; DATABASES, PROTEIN; PROTEIN BINDING; PROTEINS; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SOLVENTS;

EID: 6344258643     PISSN: 08873585     EISSN: None     Source Type: Journal    
DOI: 10.1002/prot.20234     Document Type: Article

References (23)

1. Rost B, Sander C. Conservation and prediction of solvent accessibility in protein families. Proteins 1994;20:216-226.
2. Cuff JA, Barton GJ. Application of multiple sequence alignment profiles to improve protein secondary structure prediction. Proteins 2000;40:502-511.
3. Holbrook SR, Muskal SM, Kim SH. Predicting surface exposure of amino-acids from protein-sequence. Protein Eng 1990;3:659-665.
4. Ahmad S, Gromiha MM. NETASA: neural network based prediction of solvent accessibility. Bioinformatics 2002;18:819-824.
5. Pollastri G, Baldi P, Fariselli P, Casadio R. Prediction of coordination number and relative solvent accessibility in proteins. Proteins 2002;47:142-153.
6. Yuan Z, Burrage K, Mattick JS. Prediction of protein solvent accessibility using support vector machines. Proteins 2002;48:566-570.
7. Gianese G, Bossa F, Pascarella S. Improvement in prediction of solvent accessibility by probability profiles. Protein Eng 2003;16: 987-992.
8. Thompson MJ, Goldstein RA. Predicting solvent accessibility: higher accuracy using Bayesian statistics and optimized residue substitution classes. Proteins 1996;25:38-47.
9. Carugo O. Predicting residue solvent accessibility from protein sequence by considering the sequence environment. Protein Eng 2000;13:607-609.
10. Naderi-Manesh H, Sadeghi M, Arab S, Moosavi-Movahedi AA. Prediction of protein surface accessibility with information theory. Proteins 2001;42:452-459.
11. Li X, Pan XM. New method for accurate prediction of solvent accessibility from protein sequence. Proteins 2001;42:1-5.
12. Kim H, Park H. Prediction of protein relative solvent accessibility with support vector machines and long-range interaction 3D local descriptor. Proteins 2004;54:557-562.
13. Ahmad S, Gromiha MM, Sarai A. Real value prediction of solvent accessibility from amino acid sequence. Proteins 2003;50:629-635.
14. Samanta U, Bahadur RP, Chakrabarti P. Quantifying the accessible surface area of protein residues in their local environment. Protein Eng 2002;15:659-667.
15. Lins L, Thomas A, Brasseur R. Analysis of accessible surface of residues in proteins. Protein Sci 2003;12:1406-1417.
16. Vapnik V. The nature of statistical learning theory. New York: Springer-Verlag; 2000.
17. Smola A, Scholkopf B. A tutorial on support vector regression. NeuroCOLT Technical Report, NC-TR-1998-030, http://www. neurcolt.com; 1998.
18. Joachims T. Making large-scale SVM learning practical. In: Schölkopf B, Burges C, Smola A, editors. Advances in kernel methods - support vector learning. Cambridge, MA: MIT Press; 1999.
19. Kabsch W, Sander C. Dictionary of protein secondary structure - pattern-recognition of hydrogen-bonded and geometrical features. Biopolymers 1983;22:2577-2637.
20. Noguchi T, Akiyama Y. PDB-REPRDB: a database of representative protein chains from the Protein Data Bank (PDB) in 2003. Nucleic Acids Res 2003;31:492-493.
21. Berman HM, Westbrook J, Feng Z, Gilliland G, Bhat TN, Weissig H, Shindyalov IN, Bourne PE. The Protein Data Bank. Nucleic Acids Res 2000;28:235-242.
22. Teodorescu O, Galor T, Pillardy J, Elber R. Enriching the sequence substitution matrix by structural information. Proteins 2004;54:41-48.
23. Andrade MA, O'Donoghue SI, Rost B. Adaptation of protein surfaces to subcellular location. J Mol Biol 1998;276:517-525.