135 related articles for article (PubMed ID: 18048179)
21. Pattern recognition methods for protein functional site prediction.
Yang ZR; Wang L; Young N; Trudgian D; Chou KC
Curr Protein Pept Sci; 2005 Oct; 6(5):479-91. PubMed ID: 16248799
[TBL] [Abstract][Full Text] [Related]
22. Prediction of beta-turns at over 80% accuracy based on an ensemble of predicted secondary structures and multiple alignments.
Zheng C; Kurgan L
BMC Bioinformatics; 2008 Oct; 9():430. PubMed ID: 18847492
[TBL] [Abstract][Full Text] [Related]
23. Mining sequential patterns for protein fold recognition.
Exarchos TP; Papaloukas C; Lampros C; Fotiadis DI
J Biomed Inform; 2008 Feb; 41(1):165-79. PubMed ID: 17573243
[TBL] [Abstract][Full Text] [Related]
24. A novel fusion based on the evolutionary features for protein fold recognition using support vector machines.
Refahi MS; Mir A; Nasiri JA
Sci Rep; 2020 Sep; 10(1):14368. PubMed ID: 32873824
[TBL] [Abstract][Full Text] [Related]
25. Prediction of protein folds: extraction of new features, dimensionality reduction, and fusion of heterogeneous classifiers.
Ghanty P; Pal NR
IEEE Trans Nanobioscience; 2009 Mar; 8(1):100-10. PubMed ID: 19278932
[TBL] [Abstract][Full Text] [Related]
26. Threading using neural nEtwork (TUNE): the measure of protein sequence-structure compatibility.
Lin K; May AC; Taylor WR
Bioinformatics; 2002 Oct; 18(10):1350-7. PubMed ID: 12376379
[TBL] [Abstract][Full Text] [Related]
27. DeepSF: deep convolutional neural network for mapping protein sequences to folds.
Hou J; Adhikari B; Cheng J
Bioinformatics; 2018 Apr; 34(8):1295-1303. PubMed ID: 29228193
[TBL] [Abstract][Full Text] [Related]
28. Pcons.net: protein structure prediction meta server.
Wallner B; Larsson P; Elofsson A
Nucleic Acids Res; 2007 Jul; 35(Web Server issue):W369-74. PubMed ID: 17584798
[TBL] [Abstract][Full Text] [Related]
29. Predicting protein stability changes from sequences using support vector machines.
Capriotti E; Fariselli P; Calabrese R; Casadio R
Bioinformatics; 2005 Sep; 21 Suppl 2():ii54-8. PubMed ID: 16204125
[TBL] [Abstract][Full Text] [Related]
30. Combination of threading potentials and sequence profiles improves fold recognition.
Panchenko AR; Marchler-Bauer A; Bryant SH
J Mol Biol; 2000 Mar; 296(5):1319-31. PubMed ID: 10698636
[TBL] [Abstract][Full Text] [Related]
31. FROST: a filter-based fold recognition method.
Marin A; Pothier J; Zimmermann K; Gibrat JF
Proteins; 2002 Dec; 49(4):493-509. PubMed ID: 12402359
[TBL] [Abstract][Full Text] [Related]
32. Fold recognition by combining profile-profile alignment and support vector machine.
Han S; Lee BC; Yu ST; Jeong CS; Lee S; Kim D
Bioinformatics; 2005 Jun; 21(11):2667-73. PubMed ID: 15769835
[TBL] [Abstract][Full Text] [Related]
33. Improving protein secondary structure prediction using a multi-modal BP method.
Qu W; Sui H; Yang B; Qian W
Comput Biol Med; 2011 Oct; 41(10):946-59. PubMed ID: 21880310
[TBL] [Abstract][Full Text] [Related]
34. Using pseudo amino acid composition and binary-tree support vector machines to predict protein structural classes.
Zhang TL; Ding YS
Amino Acids; 2007 Nov; 33(4):623-9. PubMed ID: 17308864
[TBL] [Abstract][Full Text] [Related]
35. Prediction of RNA-binding residues in protein sequences using support vector machines.
Wang L; Brown SJ
Conf Proc IEEE Eng Med Biol Soc; 2006; 2006():5830-3. PubMed ID: 17946337
[TBL] [Abstract][Full Text] [Related]
36. DIALIGN-T: an improved algorithm for segment-based multiple sequence alignment.
Subramanian AR; Weyer-Menkhoff J; Kaufmann M; Morgenstern B
BMC Bioinformatics; 2005 Mar; 6():66. PubMed ID: 15784139
[TBL] [Abstract][Full Text] [Related]
37. RONN: the bio-basis function neural network technique applied to the detection of natively disordered regions in proteins.
Yang ZR; Thomson R; McNeil P; Esnouf RM
Bioinformatics; 2005 Aug; 21(16):3369-76. PubMed ID: 15947016
[TBL] [Abstract][Full Text] [Related]
38. Pcons5: combining consensus, structural evaluation and fold recognition scores.
Wallner B; Elofsson A
Bioinformatics; 2005 Dec; 21(23):4248-54. PubMed ID: 16204344
[TBL] [Abstract][Full Text] [Related]
39. PrDOS: prediction of disordered protein regions from amino acid sequence.
Ishida T; Kinoshita K
Nucleic Acids Res; 2007 Jul; 35(Web Server issue):W460-4. PubMed ID: 17567614
[TBL] [Abstract][Full Text] [Related]
40. Accurate De Novo Prediction of Protein Contact Map by Ultra-Deep Learning Model.
Wang S; Sun S; Li Z; Zhang R; Xu J
PLoS Comput Biol; 2017 Jan; 13(1):e1005324. PubMed ID: 28056090
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]
