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Items: 1 to 20 of 120

1.

Ultra-fast evaluation of protein energies directly from sequence.

Grigoryan G, Zhou F, Lustig SR, Ceder G, Morgan D, Keating AE.

PLoS Comput Biol. 2006 Jun 16;2(6):e63. Epub 2006 Jun 16.

2.

Coarse-graining protein energetics in sequence variables.

Zhou F, Grigoryan G, Lustig SR, Keating AE, Ceder G, Morgan D.

Phys Rev Lett. 2005 Sep 30;95(14):148103. Epub 2005 Sep 29.

PMID:
16241695
3.

Cluster expansion models for flexible-backbone protein energetics.

Apgar JR, Hahn S, Grigoryan G, Keating AE.

J Comput Chem. 2009 Nov 30;30(15):2402-13. doi: 10.1002/jcc.21249.

PMID:
19360809
4.

Identifying and reducing error in cluster-expansion approximations of protein energies.

Hahn S, Ashenberg O, Grigoryan G, Keating AE.

J Comput Chem. 2010 Dec;31(16):2900-14. doi: 10.1002/jcc.21585.

PMID:
20602445
5.

A fast method to sample real protein conformational space.

Feldman HJ, Hogue CW.

Proteins. 2000 May 1;39(2):112-31.

PMID:
10737933
6.

Protein structure similarity from Principle Component Correlation analysis.

Zhou X, Chou J, Wong ST.

BMC Bioinformatics. 2006 Jan 25;7:40.

7.

Fast method for estimating the energy distribution of globular states of proteins.

Cao HB, Wang CZ, Ho KM.

Phys Rev E Stat Nonlin Soft Matter Phys. 2005 Aug;72(2 Pt 1):021907. Epub 2005 Aug 22.

PMID:
16196604
8.

Computational tools for analysing structural changes in proteins in solution.

Noé F, Schwarzl SM, Fischer S, Smith JC.

Appl Bioinformatics. 2003;2(3 Suppl):S11-7.

PMID:
15130811
9.

Predicting protein function from domain content.

Forslund K, Sonnhammer EL.

Bioinformatics. 2008 Aug 1;24(15):1681-7. doi: 10.1093/bioinformatics/btn312. Epub 2008 Jun 30. Erratum in: Bioinformatics. 2009 May 1;25(9):1214.

PMID:
18591194
10.

Another look at the conditions for the extraction of protein knowledge-based potentials.

Betancourt MR.

Proteins. 2009 Jul;76(1):72-85. doi: 10.1002/prot.22320.

PMID:
19089977
11.

Support Vector Machine-based classification of protein folds using the structural properties of amino acid residues and amino acid residue pairs.

Shamim MT, Anwaruddin M, Nagarajaram HA.

Bioinformatics. 2007 Dec 15;23(24):3320-7. Epub 2007 Nov 7.

PMID:
17989092
12.

A simplified approach to disulfide connectivity prediction from protein sequences.

Vincent M, Passerini A, Labbé M, Frasconi P.

BMC Bioinformatics. 2008 Jan 14;9:20. doi: 10.1186/1471-2105-9-20.

13.

Accurate prediction for atomic-level protein design and its application in diversifying the near-optimal sequence space.

Fromer M, Yanover C.

Proteins. 2009 May 15;75(3):682-705. doi: 10.1002/prot.22280.

PMID:
19003998
14.
15.

De novo protein design: fully automated sequence selection.

Dahiyat BI, Mayo SL.

Science. 1997 Oct 3;278(5335):82-7.

16.

Protein structure alignment by deterministic annealing.

Chen L, Zhou T, Tang Y.

Bioinformatics. 2005 Jan 1;21(1):51-62. Epub 2004 Aug 12.

PMID:
15308541
17.
18.

Assessment of protein folding potentials with an evolutionary method.

de Sancho D, Rey A.

J Chem Phys. 2006 Jul 7;125(1):014904.

PMID:
16863330
19.

TOUCHSTONE II: a new approach to ab initio protein structure prediction.

Zhang Y, Kolinski A, Skolnick J.

Biophys J. 2003 Aug;85(2):1145-64.

20.

CAD-score: a new contact area difference-based function for evaluation of protein structural models.

Olechnovič K, Kulberkytė E, Venclovas C.

Proteins. 2013 Jan;81(1):149-62. doi: 10.1002/prot.24172. Epub 2012 Sep 29.

PMID:
22933340

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