Jianlin Cheng
Jianlin Cheng
Curators' Distinguished Professor and Thompson Distinguished Professor, University of Missouri
Verified email at - Homepage
Cited by
Cited by
Genome sequence of the palaeopolyploid soybean
J Schmutz, SB Cannon, J Schlueter, J Ma, T Mitros, W Nelson, DL Hyten, ...
Nature 463 (7278), 178-183, 2010
SCRATCH: a protein structure and structural feature prediction server
J Cheng, AZ Randall, MJ Sweredoski, P Baldi
Nucleic acids research 33 (suppl_2), W72-W76, 2005
Prediction of protein stability changes for single‐site mutations using support vector machines
J Cheng, A Randall, P Baldi
Proteins: Structure, Function, and Bioinformatics 62 (4), 1125-1132, 2006
A large-scale evaluation of computational protein function prediction
P Radivojac, WT Clark, TR Oron, AM Schnoes, T Wittkop, A Sokolov, ...
Nature methods 10 (3), 221-227, 2013
An expanded evaluation of protein function prediction methods shows an improvement in accuracy
Y Jiang, TR Oron, WT Clark, AR Bankapur, D D’Andrea, R Lepore, ...
Genome biology 17, 1-19, 2016
3Drefine: an interactive web server for efficient protein structure refinement
D Bhattacharya, J Nowotny, R Cao, J Cheng
Nucleic acids research 44 (W1), W406-W409, 2016
A Deep Learning Network Approach to ab initio Protein Secondary Structure Prediction
M Spencer, J Eickholt, J Cheng
IEEE/ACM Transactions on Computational Biology and Bioinformatics, 1, 2014
The CAFA challenge reports improved protein function prediction and new functional annotations for hundreds of genes through experimental screens
N Zhou, Y Jiang, TR Bergquist, AJ Lee, BZ Kacsoh, AW Crocker, ...
Genome biology 20 (1), 1-23, 2019
Improved residue contact prediction using support vector machines and a large feature set
J Cheng, P Baldi
BMC bioinformatics 8 (1), 113, 2007
Accurate prediction of protein disordered regions by mining protein structure data
J Cheng, MJ Sweredoski, P Baldi
Data Mining and Knowledge Discovery 11 (3), 213-222, 2005
A neural network approach to ordinal regression
J Cheng, Z Wang, G Pollastri
2008 IEEE International Joint Conference on Neural Networks (IEEE World …, 2008
A machine learning information retrieval approach to protein fold recognition
J Cheng, P Baldi
Bioinformatics 22 (12), 1456-1463, 2006
3Drefine: Consistent protein structure refinement by optimizing hydrogen bonding network and atomic‐level energy minimization
D Bhattacharya, J Cheng
Proteins: Structure, Function, and Bioinformatics, 2012
DeepSF: deep convolutional neural network for mapping protein sequences to folds
J Hou, B Adhikari, J Cheng
Bioinformatics 34 (8), 1295-1303, 2018
Bioinformatics Methods for Mass Spectrometry-Based Proteomics Data Analysis
C Chen, J Hou, JJ Tanner, J Cheng
International Journal of Molecular Sciences 21 (8), 2873, 2020
NNcon: improved protein contact map prediction using 2D-recursive neural networks
AN Tegge, Z Wang, J Eickholt, J Cheng
Nucleic acids research 37 (suppl 2), W515-W518, 2009
Predicting protein residue-residue contacts using deep networks and boosting
J Eickholt, J Cheng
Bioinformatics, 2012
CONFOLD: Residue‐residue contact‐guided ab initio protein folding
B Adhikari, D Bhattacharya, R Cao, J Cheng
Proteins: Structure, Function, and Bioinformatics 83 (8), 1436-1449, 2015
DNCON2: Improved protein contact prediction using two-level deep convolutional neural networks
B Adhikari, J Hou, J Cheng
Bioinformatics, 2017
DeepQA: improving the estimation of single protein model quality with deep belief networks
R Cao, D Bhattacharya, J Hou, J Cheng
BMC Bioinformatics 17 (1), 495, 2016
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