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, 1-23, 2019 | 384 | 2019 |
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 | 231 | 2020 |
DeepSF: deep convolutional neural network for mapping protein sequences to folds J Hou, B Adhikari, J Cheng Bioinformatics 34 (8), 1295-1303, 2018 | 218 | 2018 |
DNCON2: improved protein contact prediction using two-level deep convolutional neural networks B Adhikari, J Hou, J Cheng Bioinformatics 34 (9), 1466-1472, 2018 | 180 | 2018 |
DeepQA: improving the estimation of single protein model quality with deep belief networks R Cao, D Bhattacharya, J Hou, J Cheng BMC bioinformatics 17, 1-9, 2016 | 170 | 2016 |
Protein tertiary structure modeling driven by deep learning and contact distance prediction in CASP13 J Hou, T Wu, R Cao, J Cheng Proteins: Structure, Function, and Bioinformatics 87 (12), 1165-1178, 2019 | 162 | 2019 |
Improving protein fold recognition by deep learning networks T Jo, J Hou, J Eickholt, J Cheng Scientific reports 5 (1), 1-11, 2015 | 138 | 2015 |
Blind prediction of homo‐and hetero‐protein complexes: The CASP13‐CAPRI experiment MF Lensink, G Brysbaert, N Nadzirin, S Velankar, RAG Chaleil, T Gerguri, ... Proteins: Structure, Function, and Bioinformatics 87 (12), 1200-1221, 2019 | 121 | 2019 |
Deep learning to predict protein backbone structure from high-resolution cryo-EM density maps D Si, SA Moritz, J Pfab, J Hou, R Cao, L Wang, T Wu, J Cheng Scientific reports 10 (1), 4282, 2020 | 100 | 2020 |
QAcon: single model quality assessment using protein structural and contact information with machine learning techniques R Cao, B Adhikari, D Bhattacharya, M Sun, J Hou, J Cheng Bioinformatics 33 (4), 586-588, 2017 | 95 | 2017 |
Estimation of model accuracy in CASP13 J Cheng, MH Choe, A Elofsson, KS Han, J Hou, AHA Maghrabi, ... Proteins: Structure, Function, and Bioinformatics 87 (12), 1361-1377, 2019 | 93 | 2019 |
Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge CL Lawson, A Kryshtafovych, PD Adams, PV Afonine, ML Baker, ... Nature methods 18 (2), 156-164, 2021 | 81 | 2021 |
DeepGRN: prediction of transcription factor binding site across cell-types using attention-based deep neural networks C Chen, J Hou, X Shi, H Yang, JA Birchler, J Cheng BMC bioinformatics 22, 1-18, 2021 | 67 | 2021 |
Deep learning methods for protein torsion angle prediction H Li, J Hou, B Adhikari, Q Lyu, J Cheng BMC bioinformatics 18, 1-13, 2017 | 65 | 2017 |
DeepDist: real-value inter-residue distance prediction with deep residual convolutional network T Wu, Z Guo, J Hou, J Cheng BMC bioinformatics 22, 1-17, 2021 | 64 | 2021 |
Global impacts of chromosomal imbalance on gene expression in Arabidopsis and other taxa J Hou, X Shi, C Chen, MS Islam, AF Johnson, T Kanno, B Huettel, MR Yen, ... Proceedings of the National Academy of Sciences 115 (48), E11321-E11330, 2018 | 60 | 2018 |
DNSS2: Improved ab initio protein secondary structure prediction using advanced deep learning architectures Z Guo, J Hou, J Cheng Proteins: Structure, Function, and Bioinformatics 89 (2), 207-217, 2021 | 45 | 2021 |
Sequence of the supernumerary B chromosome of maize provides insight into its drive mechanism and evolution N Blavet, H Yang, H Su, P Solanský, RN Douglas, M Karafiátová, ... Proceedings of the National Academy of Sciences 118 (23), e2104254118, 2021 | 39 | 2021 |
Analysis of several key factors influencing deep learning-based inter-residue contact prediction T Wu, J Hou, B Adhikari, J Cheng Bioinformatics 36 (4), 1091-1098, 2020 | 34 | 2020 |
An overview of bioinformatics methods for modeling biological pathways in yeast J Hou, L Acharya, D Zhu, J Cheng Briefings in functional genomics 15 (2), 95-108, 2016 | 29 | 2016 |