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Items: 1 to 20 of 101

1.

ANDIS: an atomic angle- and distance-dependent statistical potential for protein structure quality assessment.

Yu Z, Yao Y, Deng H, Yi M.

BMC Bioinformatics. 2019 Jun 3;20(1):299. doi: 10.1186/s12859-019-2898-y.

2.

Diverse effects of distance cutoff and residue interval on the performance of distance-dependent atom-pair potential in protein structure prediction.

Yao Y, Gui R, Liu Q, Yi M, Deng H.

BMC Bioinformatics. 2017 Dec 8;18(1):542. doi: 10.1186/s12859-017-1983-3.

3.

Statistical mechanics-based method to extract atomic distance-dependent potentials from protein structures.

Huang SY, Zou X.

Proteins. 2011 Sep;79(9):2648-61. doi: 10.1002/prot.23086. Epub 2011 Jul 5.

PMID:
21732421
4.

What is the best reference state for designing statistical atomic potentials in protein structure prediction?

Deng H, Jia Y, Wei Y, Zhang Y.

Proteins. 2012 Aug;80(9):2311-22. doi: 10.1002/prot.24121. Epub 2012 Jun 18.

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Optimized distance-dependent atom-pair-based potential DOOP for protein structure prediction.

Chae MH, Krull F, Knapp EW.

Proteins. 2015 May;83(5):881-90. doi: 10.1002/prot.24782. Epub 2015 Mar 25.

PMID:
25693513
9.

ROTAS: a rotamer-dependent, atomic statistical potential for assessment and prediction of protein structures.

Park J, Saitou K.

BMC Bioinformatics. 2014 Sep 18;15:307. doi: 10.1186/1471-2105-15-307.

10.

Novel knowledge-based mean force potential at the profile level.

Dong Q, Wang X, Lin L.

BMC Bioinformatics. 2006 Jun 27;7:324.

11.

Improving the orientation-dependent statistical potential using a reference state.

Liu Y, Zeng J, Gong H.

Proteins. 2014 Oct;82(10):2383-93. doi: 10.1002/prot.24600. Epub 2014 Jun 3.

PMID:
24810843
12.

A pairwise residue contact area-based mean force potential for discrimination of native protein structure.

Arab S, Sadeghi M, Eslahchi C, Pezeshk H, Sheari A.

BMC Bioinformatics. 2010 Jan 9;11:16. doi: 10.1186/1471-2105-11-16.

13.

A beta-complex statistical four body contact potential combined with a hydrogen bond statistical potential recognizes the correct native structure from protein decoy sets.

Sánchez-González G, Kim JK, Kim DS, Garduño-Juárez R.

Proteins. 2013 Aug;81(8):1420-33. doi: 10.1002/prot.24293. Epub 2013 Jun 1.

PMID:
23568277
14.

GOAP: a generalized orientation-dependent, all-atom statistical potential for protein structure prediction.

Zhou H, Skolnick J.

Biophys J. 2011 Oct 19;101(8):2043-52. doi: 10.1016/j.bpj.2011.09.012.

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A distance-dependent atomic knowledge-based potential and force for discrimination of native structures from decoys.

Mirzaie M, Eslahchi C, Pezeshk H, Sadeghi M.

Proteins. 2009 Nov 1;77(2):454-63. doi: 10.1002/prot.22457.

PMID:
19452553
18.

sDFIRE: Sequence-specific statistical energy function for protein structure prediction by decoy selections.

Hoque MT, Yang Y, Mishra A, Zhou Y.

J Comput Chem. 2016 May 5;37(12):1119-24. doi: 10.1002/jcc.24298. Epub 2016 Feb 5.

PMID:
26849026
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20.

Novel nonlinear knowledge-based mean force potentials based on machine learning.

Dong Q, Zhou S.

IEEE/ACM Trans Comput Biol Bioinform. 2011 Mar-Apr;8(2):476-86. doi: 10.1109/TCBB.2010.86.

PMID:
20820079

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