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Items: 1 to 20 of 246

1.

Toward an accurate prediction of inter-residue distances in proteins using 2D recursive neural networks.

Kukic P, Mirabello C, Tradigo G, Walsh I, Veltri P, Pollastri G.

BMC Bioinformatics. 2014 Jan 10;15:6. doi: 10.1186/1471-2105-15-6.

2.

Ab initio and template-based prediction of multi-class distance maps by two-dimensional recursive neural networks.

Walsh I, Baù D, Martin AJ, Mooney C, Vullo A, Pollastri G.

BMC Struct Biol. 2009 Jan 30;9:5. doi: 10.1186/1472-6807-9-5.

3.

A two-stage approach for improved prediction of residue contact maps.

Vullo A, Walsh I, Pollastri G.

BMC Bioinformatics. 2006 Mar 30;7:180.

4.

Ab initio and homology based prediction of protein domains by recursive neural networks.

Walsh I, Martin AJ, Mooney C, Rubagotti E, Vullo A, Pollastri G.

BMC Bioinformatics. 2009 Jun 26;10:195. doi: 10.1186/1471-2105-10-195.

6.

CNNcon: improved protein contact maps prediction using cascaded neural networks.

Ding W, Xie J, Dai D, Zhang H, Xie H, Zhang W.

PLoS One. 2013 Apr 23;8(4):e61533. doi: 10.1371/journal.pone.0061533. Print 2013.

7.

GDFuzz3D: a method for protein 3D structure reconstruction from contact maps, based on a non-Euclidean distance function.

Pietal MJ, Bujnicki JM, Kozlowski LP.

Bioinformatics. 2015 Nov 1;31(21):3499-505. doi: 10.1093/bioinformatics/btv390. Epub 2015 Jun 30.

PMID:
26130575
8.

Prediction of protein beta-residue contacts by Markov logic networks with grounding-specific weights.

Lippi M, Frasconi P.

Bioinformatics. 2009 Sep 15;25(18):2326-33. doi: 10.1093/bioinformatics/btp421. Epub 2009 Jul 9.

9.

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.

10.

A comprehensive assessment of sequence-based and template-based methods for protein contact prediction.

Wu S, Zhang Y.

Bioinformatics. 2008 Apr 1;24(7):924-31. doi: 10.1093/bioinformatics/btn069. Epub 2008 Feb 22.

11.

Prediction of contact maps with neural networks and correlated mutations.

Fariselli P, Olmea O, Valencia A, Casadio R.

Protein Eng. 2001 Nov;14(11):835-43.

12.

Optimal contact definition for reconstruction of contact maps.

Duarte JM, Sathyapriya R, Stehr H, Filippis I, Lappe M.

BMC Bioinformatics. 2010 May 27;11:283. doi: 10.1186/1471-2105-11-283.

13.

Long-range information and physicality constraints improve predicted protein contact maps.

Martin AJ, Baù D, Vullo A, Walsh I, Pollastri G.

J Bioinform Comput Biol. 2008 Oct;6(5):1001-20.

PMID:
18942163
14.

Improving protein secondary structure prediction using a multi-modal BP method.

Qu W, Sui H, Yang B, Qian W.

Comput Biol Med. 2011 Oct;41(10):946-59. doi: 10.1016/j.compbiomed.2011.08.005. Epub 2011 Aug 30.

PMID:
21880310
15.

Predicting residue-residue contact maps by a two-layer, integrated neural-network method.

Xue B, Faraggi E, Zhou Y.

Proteins. 2009 Jul;76(1):176-83. doi: 10.1002/prot.22329.

16.
17.

Combining Evolutionary Information and an Iterative Sampling Strategy for Accurate Protein Structure Prediction.

Braun T, Koehler Leman J, Lange OF.

PLoS Comput Biol. 2015 Dec 29;11(12):e1004661. doi: 10.1371/journal.pcbi.1004661. eCollection 2015 Dec.

18.

Combining physicochemical and evolutionary information for protein contact prediction.

Schneider M, Brock O.

PLoS One. 2014 Oct 22;9(10):e108438. doi: 10.1371/journal.pone.0108438. eCollection 2014.

19.

Accurate prediction of solvent accessibility using neural networks-based regression.

Adamczak R, Porollo A, Meller J.

Proteins. 2004 Sep 1;56(4):753-67.

PMID:
15281128
20.

Defining an essence of structure determining residue contacts in proteins.

Sathyapriya R, Duarte JM, Stehr H, Filippis I, Lappe M.

PLoS Comput Biol. 2009 Dec;5(12):e1000584. doi: 10.1371/journal.pcbi.1000584. Epub 2009 Dec 4.

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