297 related articles for article (PubMed ID: 29492997)
21. Predicting protein-ligand binding residues with deep convolutional neural networks.
Cui Y; Dong Q; Hong D; Wang X
BMC Bioinformatics; 2019 Feb; 20(1):93. PubMed ID: 30808287
[TBL] [Abstract][Full Text] [Related]
22. Prediction of protein tertiary structures using MUFOLD.
Zhang J; He Z; Wang Q; Barz B; Kosztin I; Shang Y; Xu D
Methods Mol Biol; 2012; 815():3-13. PubMed ID: 22130979
[TBL] [Abstract][Full Text] [Related]
23. 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]
24. SPIDER2: A Package to Predict Secondary Structure, Accessible Surface Area, and Main-Chain Torsional Angles by Deep Neural Networks.
Yang Y; Heffernan R; Paliwal K; Lyons J; Dehzangi A; Sharma A; Wang J; Sattar A; Zhou Y
Methods Mol Biol; 2017; 1484():55-63. PubMed ID: 27787820
[TBL] [Abstract][Full Text] [Related]
25. Protein Secondary Structure Prediction Using Deep Convolutional Neural Fields.
Wang S; Peng J; Ma J; Xu J
Sci Rep; 2016 Jan; 6():18962. PubMed ID: 26752681
[TBL] [Abstract][Full Text] [Related]
26. RaptorX-Property: a web server for protein structure property prediction.
Wang S; Li W; Liu S; Xu J
Nucleic Acids Res; 2016 Jul; 44(W1):W430-5. PubMed ID: 27112573
[TBL] [Abstract][Full Text] [Related]
27. Single-sequence-based prediction of protein secondary structures and solvent accessibility by deep whole-sequence learning.
Heffernan R; Paliwal K; Lyons J; Singh J; Yang Y; Zhou Y
J Comput Chem; 2018 Oct; 39(26):2210-2216. PubMed ID: 30368831
[TBL] [Abstract][Full Text] [Related]
28. Prediction of protein secondary structure content using amino acid composition and evolutionary information.
Lee S; Lee BC; Kim D
Proteins; 2006 Mar; 62(4):1107-14. PubMed ID: 16345074
[TBL] [Abstract][Full Text] [Related]
29. DeepECA: an end-to-end learning framework for protein contact prediction from a multiple sequence alignment.
Fukuda H; Tomii K
BMC Bioinformatics; 2020 Jan; 21(1):10. PubMed ID: 31918654
[TBL] [Abstract][Full Text] [Related]
30. MUFOLD: A new solution for protein 3D structure prediction.
Zhang J; Wang Q; Barz B; He Z; Kosztin I; Shang Y; Xu D
Proteins; 2010 Apr; 78(5):1137-52. PubMed ID: 19927325
[TBL] [Abstract][Full Text] [Related]
31. DeepBSRPred: deep learning-based binding site residue prediction for proteins.
Nikam R; Yugandhar K; Gromiha MM
Amino Acids; 2023 Oct; 55(10):1305-1316. PubMed ID: 36574037
[TBL] [Abstract][Full Text] [Related]
32. Protein backbone angle prediction with machine learning approaches.
Kuang R; Leslie CS; Yang AS
Bioinformatics; 2004 Jul; 20(10):1612-21. PubMed ID: 14988121
[TBL] [Abstract][Full Text] [Related]
33. Analysis of deep learning methods for blind protein contact prediction in CASP12.
Wang S; Sun S; Xu J
Proteins; 2018 Mar; 86 Suppl 1(Suppl 1):67-77. PubMed ID: 28845538
[TBL] [Abstract][Full Text] [Related]
34. HYPROSP II--a knowledge-based hybrid method for protein secondary structure prediction based on local prediction confidence.
Lin HN; Chang JM; Wu KP; Sung TY; Hsu WL
Bioinformatics; 2005 Aug; 21(15):3227-33. PubMed ID: 15932901
[TBL] [Abstract][Full Text] [Related]
35. MUPRED: a tool for bridging the gap between template based methods and sequence profile based methods for protein secondary structure prediction.
Bondugula R; Xu D
Proteins; 2007 Feb; 66(3):664-70. PubMed ID: 17109407
[TBL] [Abstract][Full Text] [Related]
36. PSSM-based prediction of DNA binding sites in proteins.
Ahmad S; Sarai A
BMC Bioinformatics; 2005 Feb; 6():33. PubMed ID: 15720719
[TBL] [Abstract][Full Text] [Related]
37. DeepQA: improving the estimation of single protein model quality with deep belief networks.
Cao R; Bhattacharya D; Hou J; Cheng J
BMC Bioinformatics; 2016 Dec; 17(1):495. PubMed ID: 27919220
[TBL] [Abstract][Full Text] [Related]
38. MUFOLD-DB: a processed protein structure database for protein structure prediction and analysis.
He Z; Zhang C; Xu Y; Zeng S; Zhang J; Xu D
BMC Genomics; 2014; 15 Suppl 11(Suppl 11):S2. PubMed ID: 25559128
[TBL] [Abstract][Full Text] [Related]
39. Incorporation of non-local interactions in protein secondary structure prediction from the amino acid sequence.
Frishman D; Argos P
Protein Eng; 1996 Feb; 9(2):133-42. PubMed ID: 9005434
[TBL] [Abstract][Full Text] [Related]
40. EFG-CS: Predicting chemical shifts from amino acid sequences with protein structure prediction using machine learning and deep learning models.
Gu X; Myung Y; Rodrigues CHM; Ascher DB
Protein Sci; 2024 Aug; 33(8):e5096. PubMed ID: 38979954
[TBL] [Abstract][Full Text] [Related]
[Previous] [Next] [New Search]