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Similar articles for PubMed (Select 17061924)

1.
2.

Improving prediction of secondary structure, local backbone angles, and solvent accessible surface area of proteins by iterative deep learning.

Heffernan R, Paliwal K, Lyons J, Dehzangi A, Sharma A, Wang J, Sattar A, Yang Y, Zhou Y.

Sci Rep. 2015 Jun 22;5:11476. doi: 10.1038/srep11476.

3.

An Improved Protein Structural Prediction Method by Incorporating Both Sequence and Structure Information.

Wei L, Liao M, Gao X, Zou Q.

IEEE Trans Nanobioscience. 2014 Sep 15. [Epub ahead of print]

PMID:
25248192
4.

Protein secondary structure classification revisited: processing DSSP information with PSSC.

Zacharias J, Knapp EW.

J Chem Inf Model. 2014 Jul 28;54(7):2166-79. doi: 10.1021/ci5000856. Epub 2014 Jun 16.

PMID:
24866861
5.

The impact of structural diversity and parameterization on maps of the protein universe.

Asarnow D, Singh R.

BMC Proc. 2013 Dec 20;7(Suppl 7):S1. doi: 10.1186/1753-6561-7-S7-S1. Epub 2013 Dec 20.

6.

Proposing a highly accurate protein structural class predictor using segmentation-based features.

Dehzangi A, Paliwal K, Lyons J, Sharma A, Sattar A.

BMC Genomics. 2014;15 Suppl 1:S2. doi: 10.1186/1471-2164-15-S1-S2. Epub 2014 Jan 24.

7.

Quantitative characterization of protein tertiary motifs.

Joshi RR, Sreenath S.

J Mol Model. 2014 Jan;20(1):2077. doi: 10.1007/s00894-014-2077-z. Epub 2014 Jan 26.

PMID:
24464316
8.

SCLpredT: Ab initio and homology-based prediction of subcellular localization by N-to-1 neural networks.

Adelfio A, Volpato V, Pollastri G.

Springerplus. 2013 Oct 3;2:502. doi: 10.1186/2193-1801-2-502. eCollection 2013.

9.

SPSSM8: an accurate approach for predicting eight-state secondary structures of proteins.

Cong P, Li D, Wang Z, Tang S, Li T.

Biochimie. 2013 Dec;95(12):2460-4. doi: 10.1016/j.biochi.2013.09.007. Epub 2013 Sep 18.

PMID:
24056076
10.

Porter, PaleAle 4.0: high-accuracy prediction of protein secondary structure and relative solvent accessibility.

Mirabello C, Pollastri G.

Bioinformatics. 2013 Aug 15;29(16):2056-8. doi: 10.1093/bioinformatics/btt344. Epub 2013 Jun 14.

11.

Recurrent structural motifs in non-homologous protein structures.

Johansson MU, Zoete V, Guex N.

Int J Mol Sci. 2013 Apr 10;14(4):7795-814. doi: 10.3390/ijms14047795.

12.

Accurate prediction of protein enzymatic class by N-to-1 Neural Networks.

Volpato V, Adelfio A, Pollastri G.

BMC Bioinformatics. 2013;14 Suppl 1:S11. doi: 10.1186/1471-2105-14-S1-S11. Epub 2013 Jan 14.

13.

Structure Motivator: a tool for exploring small three-dimensional elements in proteins.

Leader DP, Milner-White EJ.

BMC Struct Biol. 2012 Oct 16;12:26. doi: 10.1186/1472-6807-12-26.

14.

Towards the improved discovery and design of functional peptides: common features of diverse classes permit generalized prediction of bioactivity.

Mooney C, Haslam NJ, Pollastri G, Shields DC.

PLoS One. 2012;7(10):e45012. doi: 10.1371/journal.pone.0045012. Epub 2012 Oct 8.

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16.

Deep architectures for protein contact map prediction.

Di Lena P, Nagata K, Baldi P.

Bioinformatics. 2012 Oct 1;28(19):2449-57. Epub 2012 Jul 30.

17.

Protein secondary structure prediction with SPARROW.

Bettella F, Rasinski D, Knapp EW.

J Chem Inf Model. 2012 Feb 27;52(2):545-56. doi: 10.1021/ci200321u. Epub 2012 Jan 23.

PMID:
22224407
18.

(φ,ψ)₂ motifs: a purely conformation-based fine-grained enumeration of protein parts at the two-residue level.

Hollingsworth SA, Lewis MC, Berkholz DS, Wong WK, Karplus PA.

J Mol Biol. 2012 Feb 10;416(1):78-93. doi: 10.1016/j.jmb.2011.12.022. Epub 2011 Dec 16.

19.

CAPS-DB: a structural classification of helix-capping motifs.

Segura J, Oliva B, Fernandez-Fuentes N.

Nucleic Acids Res. 2012 Jan;40(Database issue):D479-85. doi: 10.1093/nar/gkr879. Epub 2011 Oct 22.

20.

SCLpred: protein subcellular localization prediction by N-to-1 neural networks.

Mooney C, Wang YH, Pollastri G.

Bioinformatics. 2011 Oct 15;27(20):2812-9. doi: 10.1093/bioinformatics/btr494. Epub 2011 Aug 27.

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