These tools will no longer be maintained as of December 31, 2024. Archived website can be found here. PubMed4Hh GitHub repository can be found here. Contact NLM Customer Service if you have questions.
145 related articles for article (PubMed ID: 7897654)
1. Prediction of protein secondary structure by combining nearest-neighbor algorithms and multiple sequence alignments. Salamov AA; Solovyev VV J Mol Biol; 1995 Mar; 247(1):11-5. PubMed ID: 7897654 [TBL] [Abstract][Full Text] [Related]
2. Protein secondary structure prediction using local alignments. Salamov AA; Solovyev VV J Mol Biol; 1997 Apr; 268(1):31-6. PubMed ID: 9149139 [TBL] [Abstract][Full Text] [Related]
3. 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]
4. Combining evolutionary information and neural networks to predict protein secondary structure. Rost B; Sander C Proteins; 1994 May; 19(1):55-72. PubMed ID: 8066087 [TBL] [Abstract][Full Text] [Related]
5. Protein secondary structure prediction using nearest-neighbor methods. Yi TM; Lander ES J Mol Biol; 1993 Aug; 232(4):1117-29. PubMed ID: 8371270 [TBL] [Abstract][Full Text] [Related]
6. An integrated approach to the analysis and modeling of protein sequences and structures. III. A comparative study of sequence conservation in protein structural families using multiple structural alignments. Yang AS; Honig B J Mol Biol; 2000 Aug; 301(3):691-711. PubMed ID: 10966778 [TBL] [Abstract][Full Text] [Related]
7. Improved sequence-based prediction of protein secondary structures by combining vacuum-ultraviolet circular dichroism spectroscopy with neural network. Matsuo K; Watanabe H; Gekko K Proteins; 2008 Oct; 73(1):104-12. PubMed ID: 18395813 [TBL] [Abstract][Full Text] [Related]
8. The influence of gapped positions in multiple sequence alignments on secondary structure prediction methods. Simossis VA; Heringa J Comput Biol Chem; 2004 Dec; 28(5-6):351-66. PubMed ID: 15556476 [TBL] [Abstract][Full Text] [Related]
9. PROMALS: towards accurate multiple sequence alignments of distantly related proteins. Pei J; Grishin NV Bioinformatics; 2007 Apr; 23(7):802-8. PubMed ID: 17267437 [TBL] [Abstract][Full Text] [Related]
10. Combining the GOR V algorithm with evolutionary information for protein secondary structure prediction from amino acid sequence. Kloczkowski A; Ting KL; Jernigan RL; Garnier J Proteins; 2002 Nov; 49(2):154-66. PubMed ID: 12210997 [TBL] [Abstract][Full Text] [Related]
11. NdPASA: a novel pairwise protein sequence alignment algorithm that incorporates neighbor-dependent amino acid propensities. Wang J; Feng JA Proteins; 2005 Feb; 58(3):628-37. PubMed ID: 15616964 [TBL] [Abstract][Full Text] [Related]
12. A simple and fast approach to prediction of protein secondary structure from multiply aligned sequences with accuracy above 70%. Mehta PK; Heringa J; Argos P Protein Sci; 1995 Dec; 4(12):2517-25. PubMed ID: 8580842 [TBL] [Abstract][Full Text] [Related]
13. Prediction of alpha-turns in proteins using PSI-BLAST profiles and secondary structure information. Kaur H; Raghava GP Proteins; 2004 Apr; 55(1):83-90. PubMed ID: 14997542 [TBL] [Abstract][Full Text] [Related]
14. Combining evolutionary and structural information for local protein structure prediction. Pei J; Grishin NV Proteins; 2004 Sep; 56(4):782-94. PubMed ID: 15281130 [TBL] [Abstract][Full Text] [Related]
15. 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]
16. A neural-network based method for prediction of gamma-turns in proteins from multiple sequence alignment. Kaur H; Raghava GP Protein Sci; 2003 May; 12(5):923-9. PubMed ID: 12717015 [TBL] [Abstract][Full Text] [Related]
17. Prediction of protein secondary structure at better than 70% accuracy. Rost B; Sander C J Mol Biol; 1993 Jul; 232(2):584-99. PubMed ID: 8345525 [TBL] [Abstract][Full Text] [Related]
18. Prediction of protein secondary structure content for the twilight zone sequences. Homaeian L; Kurgan LA; Ruan J; Cios KJ; Chen K Proteins; 2007 Nov; 69(3):486-98. PubMed ID: 17623861 [TBL] [Abstract][Full Text] [Related]
19. 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]
20. Prediction of protein structure by evaluation of sequence-structure fitness. Aligning sequences to contact profiles derived from three-dimensional structures. Ouzounis C; Sander C; Scharf M; Schneider R J Mol Biol; 1993 Aug; 232(3):805-25. PubMed ID: 8355272 [TBL] [Abstract][Full Text] [Related] [Next] [New Search]