Distill: A suite of web servers for the prediction of one-, two- and three-dimensional structural features of proteins

BMC Bioinformatics

Volumn 7, Issue , 2006, Pages

  Baú, David ^a   Martin, Alberto J M ^a   Mooney, Catherine ^a   Vullo, Alessandro ^a   Walsh, Ian ^a   Pollastri, Gianluca ^a  

^a UNIVERSITY COLLEGE DUBLIN   (Ireland)

Author keywords

[No Author keywords available]

Indexed keywords

HOMOLOGY INFORMATION; PROTEIN DATA BANK; PROTEIN SEQUENCES; RECURSIVE NEURAL NETWORKS; SECONDARY STRUCTURES; SOLVENT ACCESSIBILITY; STRUCTURAL FEATURE; STRUCTURAL MOTIFS;

AMINO ACIDS; FORECASTING; NEURAL NETWORKS;

PROTEINS;

AMINO ACID; PROTEIN C; SOLVENT;

ACCURACY; AMINO ACID SEQUENCE; ARTICLE; COMPUTER PROGRAM; E-MAIL; INTERNET; PREDICTION; PROTEIN ANALYSIS; PROTEIN LOCALIZATION; PROTEIN MOTIF; PROTEIN STRUCTURE; RELIABILITY; SEQUENCE HOMOLOGY; ALGORITHM; PROTEIN CONFORMATION; PROTEIN DATABASE; PROTEIN FOLDING; PROTEIN SECONDARY STRUCTURE; SEQUENCE ALIGNMENT;

ORA;

ALGORITHMS; AMINO ACID MOTIFS; AMINO ACID SEQUENCE; DATABASES, PROTEIN; INTERNET; PROTEIN CONFORMATION; PROTEIN FOLDING; PROTEIN INTERACTION MAPPING; PROTEIN STRUCTURE, SECONDARY; SEQUENCE ALIGNMENT; SOLVENTS;

EID: 33749139123     PISSN: 14712105     EISSN: 14712105     Source Type: Journal    
DOI: 10.1186/1471-2105-7-402     Document Type: Article

References (26)

1. Jones D: Gen THREADER: an efficient and reliable protein fold recognition method for genomic sequences. J Mol Biol 1999, 287:797-815.
2. Przybylski D, Rost B: Improving fold recognition without folds. J Mol Biol 2004, 341:255-269.
3. Bradley P, Chivian D, Meiler J, Misura K, Rohl C, Schief W, Wedemeyer W, Schueler-Furman O, Murphy P, Schonbrun J,.Strauss C, Baker D: Rosetta predictions in CASP5: Successes, failures, and prospects for complete automation. Proteins 2003, 53(S6):457-68.
4. Vullo A, Walsh I, Pollastri G: A two-stage approach for improved prediction of residue contact maps. BMC Bioinformatics 2006, 7(180):.
5. Mooney C, Vullo A, Pollastri G: Protein Structural Motif Prediction in Multidimensional φ - ψ Space leads to improved Secondary Structure Prediction. Journal of Computational Biologyin in press.
6. Pollastri G, Vullo A, Frasconi P, Baldi R Modular DAG-RNN Architectures for Assembling Coarse Protein Structures. Journal of Computational Biology 2006, 13(3):631-650.
7. Pollastri G, McLysaght A: Porter: a new, accurate server for protein secondary structure prediction. Bioinformatics 2005, 21(8):1719-20.
8. Baldi P, Pollastri G: The Principled Design of Large-Scale Recursive Neural Network Architectures - DAG-RNNs and the Protein Structure Prediction Problem. Journal of Machine Learning Research 2003, 4:575-602.
9. Baldi P, Brunak S, Frasconi R Soda G, Pollastri G: Exploiting the past and the future in protein secondary structure prediction. Bioinformatics 1999, 15:937-946.
10. Pollastri G, Baldi P: Prediction of Contact Maps by Recurrent Neural Network Architectures and Hidden Context Propagation from All Four Cardinal Corners. Bioinformatics 2002, 18(Suppl 1):S62-S70.
11. Pollastri G, Baú D, Vullo A: DISTILL. A Machine Learning Approach to Ab Initio Protein Structure Prediction. In Analysis of Biological Data. A Soft Computing Approach Edited by: Bandyopadhyay S, Maulik U, Wang J. World Scientific in press.
12. Berman H, Westbrook J, Feng Z, Gilliland G, Bhat T, Weissig H, Shindyalov I, Bourne P: The Protein Data Bank. Nucl Acids Res 2000, 28:235-242 [http://pdbbeta.rcsb.org/pdb/Welcome.do].
13. Vendruscolo M, Kussell E, Domany E: Recovery of protein structure from contact maps. Folding and Design 1997, 2:295-306.
14. Hobohm U, Sander C: Enlarged representative set of protein structures. Protein Sci 1994, 3:522-24 [http://bioinfo.tg.fh-giessen.de/pdbselect/]
15. Kabsch W, Sander C: Dictionary of protein secondary structure: pattern recognition of hydrogen-bonded and geometrical features. Biopolymers 1983, 22:2577-2637.
16. Altschul S, Madden T, Schaffer,A: Gapped BLAST and PSI-BLAST: a new generation of protein database search programs. Nucl Acids Res 1997, 25:3389-3402.
17. Pollastri G, Przybylski D, Rost B, Baldi P: Improving the prediction of protein secondary structure in three and eight classes using recurrent neural networks and profiles. Proteins 2002, 47:228-235.
18. Pollastri G, Martin AJM, Mooney C, Vullo A. High-throughput comparative modelling of protein secondary structure and solvent accessibility. submitted
19. Sims GE, Choi I, Kim S: Protein conformational space in higher order ψ-φ maps. PNAS 2005, 18:618-621.
20. Vincent J, Tai C, Sathyanarayana B, Lee B: Assessment of CASP6 Predictions for New and Nearly New Fold Targets. Proteins 2006, 61 (S7):67-83.
21. Distill [Http://distill.ucd.ie/distill/]
22. Sayle R Milner-White E: RasMol: Biomolecular graphics for all. TIBS 1995, 20(9):-374.
23. Zhang Y, Skolnik J: Scoring function for automated assessment of protein structure template quality. Proteins 2004, 57(4):702-710.
24. Eyrich V, Marti-Renom M, Przybylski D, Madhusudan M, Fiser A, Pazos F, Valencia A, Sali A, Rost B: EVA: continuous automatic evaluation od protein structure prediction servers. Bioinformatics 2001, 17:1242-1251.
25. Ceroni A, Frasconi P, Pollastri G: Learning Protein Secondary Structure from Sequential and Relational Data. Neural Networks 2005, 18(8):1029-39.
26. Moult J, Fidelis K, Zemla A, Hubbard T. Critical assessment of methods of protein structure prediction (CASP)-round V. Proteins 2003, 53(S6):334-9.