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Items: 1 to 20 of 119

1.

Enhancing the accuracy of HMM-based conserved pathway prediction using global correspondence scores.

Qian X, Sahraeian SM, Yoon BJ.

BMC Bioinformatics. 2011 Oct 18;12 Suppl 10:S6. doi: 10.1186/1471-2105-12-S10-S6.

2.

Accurate multiple network alignment through context-sensitive random walk.

Jeong H, Yoon BJ.

BMC Syst Biol. 2015;9 Suppl 1:S7. doi: 10.1186/1752-0509-9-S1-S7. Epub 2015 Jan 21.

3.

Seed selection strategy in global network alignment without destroying the entire structures of functional modules.

Wang B, Gao L.

Proteome Sci. 2012 Jun 21;10 Suppl 1:S16. doi: 10.1186/1477-5956-10-S1-S16.

4.

Effective identification of conserved pathways in biological networks using hidden Markov models.

Qian X, Yoon BJ.

PLoS One. 2009 Dec 7;4(12):e8070. doi: 10.1371/journal.pone.0008070.

5.

Comparative analysis of protein interaction networks reveals that conserved pathways are susceptible to HIV-1 interception.

Qian X, Yoon BJ.

BMC Bioinformatics. 2011 Feb 15;12 Suppl 1:S19. doi: 10.1186/1471-2105-12-S1-S19.

6.

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.

PMID:
9322022
7.

RESQUE: network reduction using semi-Markov random walk scores for efficient querying of biological networks.

Sahraeian SM, Yoon BJ.

Bioinformatics. 2012 Aug 15;28(16):2129-36. doi: 10.1093/bioinformatics/bts341. Epub 2012 Jun 23.

9.

Scalable global alignment for multiple biological networks.

Shih YK, Parthasarathy S.

BMC Bioinformatics. 2012 Mar 21;13 Suppl 3:S11. doi: 10.1186/1471-2105-13-S3-S11.

10.

A fast approach to global alignment of protein-protein interaction networks.

Kollias G, Sathe M, Mohammadi S, Grama A.

BMC Res Notes. 2013 Jan 31;6:35. doi: 10.1186/1756-0500-6-35.

11.

Global network alignment using multiscale spectral signatures.

Patro R, Kingsford C.

Bioinformatics. 2012 Dec 1;28(23):3105-14. doi: 10.1093/bioinformatics/bts592. Epub 2012 Oct 9.

12.

Global alignment of multiple protein interaction networks with application to functional orthology detection.

Singh R, Xu J, Berger B.

Proc Natl Acad Sci U S A. 2008 Sep 2;105(35):12763-8. doi: 10.1073/pnas.0806627105. Epub 2008 Aug 25.

13.

Fitting hidden Markov models of protein domains to a target species: application to Plasmodium falciparum.

Terrapon N, Gascuel O, Maréchal E, Bréhélin L.

BMC Bioinformatics. 2012 May 1;13:67. doi: 10.1186/1471-2105-13-67.

14.
15.

Predicting conserved protein motifs with Sub-HMMs.

Horan K, Shelton CR, Girke T.

BMC Bioinformatics. 2010 Apr 26;11:205. doi: 10.1186/1471-2105-11-205.

16.

Automated protein subfamily identification and classification.

Brown DP, Krishnamurthy N, Sjölander K.

PLoS Comput Biol. 2007 Aug;3(8):e160.

17.

Graemlin: general and robust alignment of multiple large interaction networks.

Flannick J, Novak A, Srinivasan BS, McAdams HH, Batzoglou S.

Genome Res. 2006 Sep;16(9):1169-81. Epub 2006 Aug 9.

18.

Training HMM structure with genetic algorithm for biological sequence analysis.

Won KJ, Prügel-Bennett A, Krogh A.

Bioinformatics. 2004 Dec 12;20(18):3613-9. Epub 2004 Aug 5.

19.

Sequence alignment by passing messages.

Yoon BJ.

BMC Genomics. 2014;15 Suppl 1:S14. doi: 10.1186/1471-2164-15-S1-S14. Epub 2014 Jan 24.

20.

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 21;8:357.

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