Method - Protein Homology Detection Through Alignment of Markov Random Fields - page 29

References

1. Altschul, S.F., et al.: Gapped BLAST and PSI-BLAST: a new generation of protein database
search programs. Nucleic Acids Res. 25(17), 3389 3402 (1997)

2. Marks, D.S., et al.: Protein 3D structure computed from evolutionary sequence variation. PLoS
ONE 6(12), e28766 (2011)
3. Jones, D.T., et al.: PSICOV: precise structural contact prediction using sparse inverse
covariance estimation on large multiple sequence alignments. Bioinformatics 28(2), 184 - 190
(2012)
4. Wang, Z., Xu, J.: Predicting protein contact map using evolutionary and physical constraints
by integer programming. Bioinformatics 29(13), i266-i273 - i266-i273 (2013)
5. Zhao, F., Xu, J.: A position-speci c distance-dependent statistical potential for protein
structure and functional study. Structure 20(6), 1118 - 1126 (2012)
6. Faraggi, E., Xue, B., Zhou, Y.: Improving the prediction accuracy of residue solvent
accessibility and real-value backbone torsion angles of proteins by guided-learning through a
two-layer neural network. Proteins Struct. Funct. Bioinf. 74(4), 847

-

856 (2009)
7. Malouf, R.: A comparison of algorithms for maximum entropy parameter estimation. In:
Proceedings of the 6th Conference on Natural Language Learning, vol. 20. Association for
Computational Linguistics (2002)
8. Ekeberg, M., Hartonen, T., Aurell, E.: Fast pseudo likelihood maximization for direct-
coupling analysis of protein structure from many homologous amino-acid sequences. arXiv
preprint arXiv:1401.4832 (2014)
9. Kamisetty, H., Ovchinnikov, S., Baker, D.: Assessing the utility of coevolution-based residue

-

-
residue contact predictions in a sequence-and structure-rich era. Proc. Natl. Acad. Sci. 110
(39), 15674 - 15679 (2013)
10. Lathrop, R.H.: The protein threading problem with sequence amino acid interaction
preferences is NP-complete. Protein Eng. 7(9), 1059 - 1068 (1994)
11. Boyd, S., et al.: Distributed optimization and statistical learning via the alternating direction
method of multipliers. Found. Trends ® Mach. Learn. 3(1), 1 - 122 (2011)
12. Peng, J., Bo, L., Xu, J.: Conditional neural fields. In: Advances in Neural Information
Processing Systems (2009)
13. Ma, J., et al.: Protein threading using context-specific alignment potential. Bioinformatics 29
(13), i257-i265

i257-i265 (2013)
14. Ma, J., et al.: A conditional neural fields model for protein threading. Bioinformatics 28(12),
i59-i66

-

i59-i66 (2012)
15. Wang, S., et al.: Protein structure alignment beyond spatial proximity, vol. 3. Science Report
(2013)
16. Henikoff, S., Henikoff, J.G.: Amino acid substitution matrices from protein blocks. Proc. Natl.
Acad. Sci. 89(22), 10915

-

10919 (1992)

-

17. Prli , A., Domingues, F.S., Sippl, M.J.: Structure-derived substitution matrices for alignment

of distantly related sequences. Protein Eng. 13(8), 545

ć

550 (2000)
18. Tan, Y.H., Huang, H., Kihara, D.: Statistical potential-based amino acid similarity matrices for
aligning distantly related protein sequences. Proteins Struct. Funct. Bioinf. 64(3), 587 - 600
(2006)
19. Shen, M.Y., Sali, A.: Statistical potential for assessment and prediction of protein structures.
Protein Sci. 15(11), 2507 - 2524 (2006)
20. Zhang, J., Zhang, Y.: A novel side-chain orientation dependent potential derived from
random-walk reference state for protein fold selection and structure prediction. PLoS ONE 5
(10), e15386 (2010)

-