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Items: 1 to 20 of 26

1.

Benchmarking Deep Networks for Predicting Residue-Specific Quality of Individual Protein Models in CASP11.

Liu T, Wang Y, Eickholt J, Wang Z.

Sci Rep. 2016 Jan 14;6:19301. doi: 10.1038/srep19301.

2.

Improving Protein Fold Recognition by Deep Learning Networks.

Jo T, Hou J, Eickholt J, Cheng J.

Sci Rep. 2015 Dec 4;5:17573. doi: 10.1038/srep17573.

3.

An Overview of Practical Applications of Protein Disorder Prediction and Drive for Faster, More Accurate Predictions.

Deng X, Gumm J, Karki S, Eickholt J, Cheng J.

Int J Mol Sci. 2015 Jul 7;16(7):15384-404. doi: 10.3390/ijms160715384.

4.

Characterizing the Discussion of Antibiotics in the Twittersphere: What is the Bigger Picture?

Kendra RL, Karki S, Eickholt JL, Gandy L.

J Med Internet Res. 2015 Jun 19;17(6):e154. doi: 10.2196/jmir.4220.

5.

A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction.

Spencer M, Eickholt J, Jianlin Cheng.

IEEE/ACM Trans Comput Biol Bioinform. 2015 Jan-Feb;12(1):103-12. doi: 10.1109/TCBB.2014.2343960. Epub 2014 Aug 7.

6.

PCP-ML: protein characterization package for machine learning.

Eickholt J, Wang Z.

BMC Res Notes. 2014 Nov 18;7:810. doi: 10.1186/1756-0500-7-810.

7.

The MULTICOM protein tertiary structure prediction system.

Li J, Bhattacharya D, Cao R, Adhikari B, Deng X, Eickholt J, Cheng J.

Methods Mol Biol. 2014;1137:29-41. doi: 10.1007/978-1-4939-0366-5_3.

PMID:
24573472
8.

A study and benchmark of DNcon: a method for protein residue-residue contact prediction using deep networks.

Eickholt J, Cheng J.

BMC Bioinformatics. 2013;14 Suppl 14:S12. doi: 10.1186/1471-2105-14-S14-S12. Epub 2013 Oct 9.

9.

DNdisorder: predicting protein disorder using boosting and deep networks.

Eickholt J, Cheng J.

BMC Bioinformatics. 2013 Mar 6;14:88. doi: 10.1186/1471-2105-14-88.

10.

Designing and benchmarking the MULTICOM protein structure prediction system.

Li J, Deng X, Eickholt J, Cheng J.

BMC Struct Biol. 2013 Feb 27;13:2. doi: 10.1186/1472-6807-13-2.

11.

Predicting protein residue-residue contacts using deep networks and boosting.

Eickholt J, Cheng J.

Bioinformatics. 2012 Dec 1;28(23):3066-72. doi: 10.1093/bioinformatics/bts598. Epub 2012 Oct 9.

12.

Recursive protein modeling: a divide and conquer strategy for Protein Structure Prediction and its case study in CASP9.

Cheng J, Eickholt J, Wang Z, Deng X.

J Bioinform Comput Biol. 2012 Jun;10(3):1242003. doi: 10.1142/S0219720012420036.

13.

The MULTICOM toolbox for protein structure prediction.

Cheng J, Li J, Wang Z, Eickholt J, Deng X.

BMC Bioinformatics. 2012 Apr 30;13:65. doi: 10.1186/1471-2105-13-65.

14.

A conformation ensemble approach to protein residue-residue contact.

Eickholt J, Wang Z, Cheng J.

BMC Struct Biol. 2011 Oct 12;11:38. doi: 10.1186/1472-6807-11-38.

15.

A comprehensive overview of computational protein disorder prediction methods.

Deng X, Eickholt J, Cheng J.

Mol Biosyst. 2012 Jan;8(1):114-21. doi: 10.1039/c1mb05207a. Epub 2011 Aug 26. Review.

16.

APOLLO: a quality assessment service for single and multiple protein models.

Wang Z, Eickholt J, Cheng J.

Bioinformatics. 2011 Jun 15;27(12):1715-6. doi: 10.1093/bioinformatics/btr268. Epub 2011 May 5.

17.

DoBo: Protein domain boundary prediction by integrating evolutionary signals and machine learning.

Eickholt J, Deng X, Cheng J.

BMC Bioinformatics. 2011 Feb 1;12:43. doi: 10.1186/1471-2105-12-43.

18.

MULTICOM: a multi-level combination approach to protein structure prediction and its assessments in CASP8.

Wang Z, Eickholt J, Cheng J.

Bioinformatics. 2010 Apr 1;26(7):882-8. doi: 10.1093/bioinformatics/btq058. Epub 2010 Feb 11.

19.

PreDisorder: ab initio sequence-based prediction of protein disordered regions.

Deng X, Eickholt J, Cheng J.

BMC Bioinformatics. 2009 Dec 21;10:436. doi: 10.1186/1471-2105-10-436.

20.

Prediction of global and local quality of CASP8 models by MULTICOM series.

Cheng J, Wang Z, Tegge AN, Eickholt J.

Proteins. 2009;77 Suppl 9:181-4. doi: 10.1002/prot.22487.

PMID:
19544564
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