109 related articles for article (PubMed ID: 23292699)
1. A probabilistic model for secondary structure prediction from protein chemical shifts.
Mechelke M; Habeck M
Proteins; 2013 Jun; 81(6):984-93. PubMed ID: 23292699
[TBL] [Abstract][Full Text] [Related]
2. A Segmental Semi Markov Model for protein secondary structure prediction.
Malekpour SA; Naghizadeh S; Pezeshk H; Sadeghi M; Eslahchi C
Math Biosci; 2009 Oct; 221(2):130-5. PubMed ID: 19646454
[TBL] [Abstract][Full Text] [Related]
3. Analysis of an optimal hidden Markov model for secondary structure prediction.
Martin J; Gibrat JF; Rodolphe F
BMC Struct Biol; 2006 Dec; 6():25. PubMed ID: 17166267
[TBL] [Abstract][Full Text] [Related]
4. Incorporating global information into secondary structure prediction with hidden Markov models of protein folds.
Di Francesco V; McQueen P; Garnier J; Munson PJ
Proc Int Conf Intell Syst Mol Biol; 1997; 5():100-3. PubMed ID: 9322022
[TBL] [Abstract][Full Text] [Related]
5. Hydrogen bonding on the ice-binding face of a beta-helical antifreeze protein indicated by amide proton NMR chemical shifts.
Daley ME; Graether SP; Sykes BD
Biochemistry; 2004 Oct; 43(41):13012-7. PubMed ID: 15476394
[TBL] [Abstract][Full Text] [Related]
6. Evaluation of methods for predicting the topology of beta-barrel outer membrane proteins and a consensus prediction method.
Bagos PG; Liakopoulos TD; Hamodrakas SJ
BMC Bioinformatics; 2005 Jan; 6():7. PubMed ID: 15647112
[TBL] [Abstract][Full Text] [Related]
7. Sequence-based protein structure prediction using a reduced state-space hidden Markov model.
Lampros C; Costas Papaloukas ; Exarchos TP; Yorgos Goletsis ; Fotiadis DI
Comput Biol Med; 2007 Sep; 37(9):1211-24. PubMed ID: 17161834
[TBL] [Abstract][Full Text] [Related]
8. An evolutionary method for learning HMM structure: prediction of protein secondary structure.
Won KJ; Hamelryck T; Prügel-Bennett A; Krogh A
BMC Bioinformatics; 2007 Sep; 8():357. PubMed ID: 17888163
[TBL] [Abstract][Full Text] [Related]
9. Protein secondary structure prediction using three neural networks and a segmental semi Markov model.
Malekpour SA; Naghizadeh S; Pezeshk H; Sadeghi M; Eslahchi C
Math Biosci; 2009 Feb; 217(2):145-50. PubMed ID: 19046975
[TBL] [Abstract][Full Text] [Related]
10. Learning generative models for protein fold families.
Balakrishnan S; Kamisetty H; Carbonell JG; Lee SI; Langmead CJ
Proteins; 2011 Apr; 79(4):1061-78. PubMed ID: 21268112
[TBL] [Abstract][Full Text] [Related]
11. HMMSTR: a hidden Markov model for local sequence-structure correlations in proteins.
Bystroff C; Thorsson V; Baker D
J Mol Biol; 2000 Aug; 301(1):173-90. PubMed ID: 10926500
[TBL] [Abstract][Full Text] [Related]
12. Protein secondary structure: entropy, correlations and prediction.
Crooks GE; Brenner SE
Bioinformatics; 2004 Jul; 20(10):1603-11. PubMed ID: 14988117
[TBL] [Abstract][Full Text] [Related]
13. HMM-ModE--improved classification using profile hidden Markov models by optimising the discrimination threshold and modifying emission probabilities with negative training sequences.
Srivastava PK; Desai DK; Nandi S; Lynn AM
BMC Bioinformatics; 2007 Mar; 8():104. PubMed ID: 17389042
[TBL] [Abstract][Full Text] [Related]
14. A 9-state hidden Markov model using protein secondary structure information for protein fold recognition.
Lee SY; Lee JY; Jung KS; Ryu KH
Comput Biol Med; 2009 Jun; 39(6):527-34. PubMed ID: 19394594
[TBL] [Abstract][Full Text] [Related]
15. Predicting protein secondary structure by a support vector machine based on a new coding scheme.
Wang LH; Liu J; Li YF; Zhou HB
Genome Inform; 2004; 15(2):181-90. PubMed ID: 15706504
[TBL] [Abstract][Full Text] [Related]
16. A neural network method for prediction of beta-turn types in proteins using evolutionary information.
Kaur H; Raghava GP
Bioinformatics; 2004 Nov; 20(16):2751-8. PubMed ID: 15145798
[TBL] [Abstract][Full Text] [Related]
17. The prediction of protein structural class using averaged chemical shifts.
Lin H; Ding C; Song Q; Yang P; Ding H; Deng KJ; Chen W
J Biomol Struct Dyn; 2012; 29(6):643-9. PubMed ID: 22545995
[TBL] [Abstract][Full Text] [Related]
18. Toward direct determination of conformations of protein building units from multidimensional NMR experiments VI: chemical shift analysis of his to gain 3D structure and protonation state information.
Hudáky P; Perczel A
J Comput Chem; 2005 Oct; 26(13):1307-17. PubMed ID: 15999335
[TBL] [Abstract][Full Text] [Related]
19. A dynamic Bayesian network approach to protein secondary structure prediction.
Yao XQ; Zhu H; She ZS
BMC Bioinformatics; 2008 Jan; 9():49. PubMed ID: 18218144
[TBL] [Abstract][Full Text] [Related]
20. Nearest-neighbor effects on backbone alpha and beta carbon chemical shifts in proteins.
Wang L; Eghbalnia HR; Markley JL
J Biomol NMR; 2007 Nov; 39(3):247-57. PubMed ID: 17899393
[TBL] [Abstract][Full Text] [Related]
[Next] [New Search]
