161 related articles for article (PubMed ID: 26371555)
1. Codon-level information improves predictions of inter-residue contacts in proteins by correlated mutation analysis.
Jacob E; Unger R; Horovitz A
Elife; 2015 Sep; 4():e08932. PubMed ID: 26371555
[TBL] [Abstract][Full Text] [Related]
2. Improving protein-protein interaction prediction using evolutionary information from low-quality MSAs.
Várnai C; Burkoff NS; Wild DL
PLoS One; 2017; 12(2):e0169356. PubMed ID: 28166227
[TBL] [Abstract][Full Text] [Related]
3. Predicting protein β-sheet contacts using a maximum entropy-based correlated mutation measure.
Burkoff NS; Várnai C; Wild DL
Bioinformatics; 2013 Mar; 29(5):580-7. PubMed ID: 23314126
[TBL] [Abstract][Full Text] [Related]
4. Improving contact predictions by the combination of correlated mutations and other sources of sequence information.
Olmea O; Valencia A
Fold Des; 1997; 2(3):S25-32. PubMed ID: 9218963
[TBL] [Abstract][Full Text] [Related]
5. DNCON2_Inter: predicting interchain contacts for homodimeric and homomultimeric protein complexes using multiple sequence alignments of monomers and deep learning.
Quadir F; Roy RS; Halfmann R; Cheng J
Sci Rep; 2021 Jun; 11(1):12295. PubMed ID: 34112907
[TBL] [Abstract][Full Text] [Related]
6. Forecasting residue-residue contact prediction accuracy.
Wozniak PP; Konopka BM; Xu J; Vriend G; Kotulska M
Bioinformatics; 2017 Nov; 33(21):3405-3414. PubMed ID: 29036497
[TBL] [Abstract][Full Text] [Related]
7. De novo structure prediction of globular proteins aided by sequence variation-derived contacts.
Kosciolek T; Jones DT
PLoS One; 2014; 9(3):e92197. PubMed ID: 24637808
[TBL] [Abstract][Full Text] [Related]
8. Linear predictive coding representation of correlated mutation for protein sequence alignment.
Jeong CS; Kim D
BMC Bioinformatics; 2010 Apr; 11 Suppl 2(Suppl 2):S2. PubMed ID: 20406500
[TBL] [Abstract][Full Text] [Related]
9. Protein Residue Contacts and Prediction Methods.
Adhikari B; Cheng J
Methods Mol Biol; 2016; 1415():463-76. PubMed ID: 27115648
[TBL] [Abstract][Full Text] [Related]
10. Prediction of distant residue contacts with the use of evolutionary information.
Vicatos S; Reddy BV; Kaznessis Y
Proteins; 2005 Mar; 58(4):935-49. PubMed ID: 15645442
[TBL] [Abstract][Full Text] [Related]
11. Prediction of protein contacts from correlated sequence substitutions.
Sadowski MI; Taylor WR
Sci Prog; 2013; 96(Pt 1):33-42. PubMed ID: 23738436
[TBL] [Abstract][Full Text] [Related]
12. Protein contact prediction by integrating deep multiple sequence alignments, coevolution and machine learning.
Adhikari B; Hou J; Cheng J
Proteins; 2018 Mar; 86 Suppl 1(Suppl 1):84-96. PubMed ID: 29047157
[TBL] [Abstract][Full Text] [Related]
13. Accurate simulation and detection of coevolution signals in multiple sequence alignments.
Ackerman SH; Tillier ER; Gatti DL
PLoS One; 2012; 7(10):e47108. PubMed ID: 23091608
[TBL] [Abstract][Full Text] [Related]
14. Gleaning structural and functional information from correlations in protein multiple sequence alignments.
Neuwald AF
Curr Opin Struct Biol; 2016 Jun; 38():1-8. PubMed ID: 27179293
[TBL] [Abstract][Full Text] [Related]
15. ComplexContact: a web server for inter-protein contact prediction using deep learning.
Zeng H; Wang S; Zhou T; Zhao F; Li X; Wu Q; Xu J
Nucleic Acids Res; 2018 Jul; 46(W1):W432-W437. PubMed ID: 29790960
[TBL] [Abstract][Full Text] [Related]
16. Evaluation of residue-residue contact prediction methods: From retrospective to prospective.
Zhang H; Bei Z; Xi W; Hao M; Ju Z; Saravanan KM; Zhang H; Guo N; Wei Y
PLoS Comput Biol; 2021 May; 17(5):e1009027. PubMed ID: 34029314
[TBL] [Abstract][Full Text] [Related]
17. Correlated mutations and residue contacts in proteins.
Göbel U; Sander C; Schneider R; Valencia A
Proteins; 1994 Apr; 18(4):309-17. PubMed ID: 8208723
[TBL] [Abstract][Full Text] [Related]
18. Analysis of covariation in an SH3 domain sequence alignment: applications in tertiary contact prediction and the design of compensating hydrophobic core substitutions.
Larson SM; Di Nardo AA; Davidson AR
J Mol Biol; 2000 Oct; 303(3):433-46. PubMed ID: 11031119
[TBL] [Abstract][Full Text] [Related]
19. Use of estimated evolutionary strength at the codon level improves the prediction of disease-related protein mutations in humans.
Capriotti E; Arbiza L; Casadio R; Dopazo J; Dopazo H; Marti-Renom MA
Hum Mutat; 2008 Jan; 29(1):198-204. PubMed ID: 17935148
[TBL] [Abstract][Full Text] [Related]
20. PSICOV: precise structural contact prediction using sparse inverse covariance estimation on large multiple sequence alignments.
Jones DT; Buchan DW; Cozzetto D; Pontil M
Bioinformatics; 2012 Jan; 28(2):184-90. PubMed ID: 22101153
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
