The MicroArray Quality Control (MAQC)-II study of common practices for the development and validation of microarray-based predictive models L Shi, G Campbell, WD Jones, F Campagne, Z Wen, SJ Walker, Z Su, ... Nature Biotechnology 28 (8), 827-838, 2010 | 876 | 2010 |
Network‐based global inference of human disease genes X Wu, R Jiang, MQ Zhang, S Li Molecular Systems Biology 4 (1), 189, 2008 | 780 | 2008 |
A random forest approach to the detection of epistatic interactions in case-control studies R Jiang, W Tang, X Wu, W Fu BMC Bioinformatics 10 (1), 1-12, 2009 | 346 | 2009 |
Clustering 16S rRNA for OTU prediction: a method of unsupervised Bayesian clustering X Hao, R Jiang, T Chen Bioinformatics 27 (5), 611-618, 2011 | 301 | 2011 |
Modeling gene regulation from paired expression and chromatin accessibility data Z Duren, X Chen, R Jiang, Y Wang, WH Wong Proceedings of the National Academy of Sciences 114 (25), E4914-E4923, 2017 | 177 | 2017 |
Research in computational molecular biology J Huang, Q Morris, B Frey Detecting microRNA targets by linking sequence, microRNA and gene expression …, 2006 | 177 | 2006 |
DeepCDR: a hybrid graph convolutional network for predicting cancer drug response Q Liu, Z Hu, R Jiang, M Zhou Bioinformatics 36 (Supplement_2), i911-i918, 2020 | 158 | 2020 |
Integrating next-generation sequencing and traditional tongue diagnosis to determine tongue coating microbiome B Jiang, X Liang, Y Chen, T Ma, L Liu, J Li, R Jiang, T Chen, X Zhang, S Li Scientific Reports 2 (1), 1-15, 2012 | 149 | 2012 |
From ontology to semantic similarity: calculation of ontology‐based semantic similarity M Gan, X Dou, R Jiang The Scientific World Journal 2013 (1), 793091, 2013 | 147 | 2013 |
Predicting enhancers with deep convolutional neural networks X Min, W Zeng, S Chen, N Chen, T Chen, R Jiang BMC Bioinformatics 18 (13), 35-46, 2017 | 144* | 2017 |
Epistatic module detection for case-control studies: a Bayesian model with a Gibbs sampling strategy W Tang, X Wu, R Jiang, Y Li PLoS Genetics 5 (5), e1000464, 2009 | 144 | 2009 |
Reconstructing cell cycle pseudo time-series via single-cell transcriptome data Z Liu, H Lou, K Xie, H Wang, N Chen, OM Aparicio, MQ Zhang, R Jiang, ... Nature Communications 8 (1), 1-9, 2017 | 131 | 2017 |
Align human interactome with phenome to identify causative genes and networks underlying disease families X Wu, Q Liu, R Jiang Bioinformatics 25 (1), 98-104, 2009 | 121 | 2009 |
DeepTACT: predicting 3D chromatin contacts via bootstrapping deep learning W Li, WH Wong, R Jiang Nucleic Acids Research 47 (10), e60-e60, 2019 | 120 | 2019 |
Chromatin accessibility prediction via convolutional long short-term memory networks with k-mer embedding X Min, W Zeng, N Chen, T Chen, R Jiang Bioinformatics 33 (14), i92-i101, 2017 | 119 | 2017 |
Density estimation using deep generative neural networks Q Liu, J Xu, R Jiang, WH Wong Proceedings of the National Academy of Sciences 118 (15), e2101344118, 2021 | 111 | 2021 |
Prediction of deleterious nonsynonymous single‐nucleotide polymorphism for human diseases J Wu, R Jiang The Scientific World Journal 2013 (1), 675851, 2013 | 92 | 2013 |
Uncover disease genes by maximizing information flow in the phenome–interactome network Y Chen, T Jiang, R Jiang Bioinformatics 27 (13), i167-i176, 2011 | 92 | 2011 |
Prediction of enhancer-promoter interactions via natural language processing W Zeng, M Wu, R Jiang BMC Genomics 19 (2), 13-22, 2018 | 91 | 2018 |
Constructing a gene semantic similarity network for the inference of disease genes R Jiang, M Gan, P He BMC Systems Biology 5 (2), 1-11, 2011 | 90 | 2011 |