|A comprehensive assessment of RNA-seq accuracy, reproducibility and information content by the Sequencing Quality Control Consortium|
Nature Biotechnology 32, 903–914, 2014
|A rat RNA-Seq transcriptomic BodyMap across 11 organs and 4 developmental stages|
Y Yu, JC Fuscoe, C Zhao, C Guo, M Jia, T Qing, DI Bannon, L Lancashire, ...
Nature communications 5 (1), 1-11, 2014
|Comparison of RNA-seq and microarray-based models for clinical endpoint prediction|
W Zhang, Y Yu, F Hertwig, J Thierry-Mieg, W Zhang, D Thierry-Mieg, ...
Genome Biology 16 (1), 133, 2015
|DRAR-CPI: a server for identifying drug repositioning potential and adverse drug reactions via the chemical–protein interactome|
H Luo, J Chen, L Shi, M Mikailov, H Zhu, K Wang, L He, L Yang
Nucleic acids research 39 (suppl_2), W492-W498, 2011
|Exploring off-targets and off-systems for adverse drug reactions via chemical-protein interactome—clozapine-induced agranulocytosis as a case study|
L Yang, K Wang, J Chen, AG Jegga, H Luo, L Shi, C Wan, X Guo, S Qin, ...
PLoS Computational Biology 7 (3), e1002016, 2011
|Molecular docking to identify associations between drugs and Class I human leukocyte antigens for predicting idiosyncratic drug reactions|
H Luo, T Du, P Zhou, L Yang, H Mei, HW Ng, W Zhang, M Shu, W Tong, ...
Comb Chem High Throughput Screen. 18 (3), 296-304(9), 2015
|DDI-CPI, a server that predicts drug–drug interactions through implementing the chemical–protein interactome|
H Luo, P Zhang, H Huang, J Huang, E Kao, L Shi, L He, L Yang
Nucleic acids research 42 (W1), W46-W52, 2014
|Drug repositioning for diabetes based on 'omics' data mining|
M Zhang, H Luo, Z Xi, E Rogaeva
PLOS ONE 10 (5), e0126082, 2015
|SePreSA: a server for the prediction of populations susceptible to serious adverse drug reactions implementing the methodology of a chemical–protein interactome|
L Yang, H Luo, J Chen, Q Xing, L He
Nucleic acids research 37 (suppl_2), W406-W412, 2009
|Interpretable drug target prediction using deep neural representation|
Y Gao, A Fokoue, H Luo, A Iyengar, S Dey, P Zhang
Proceedings of IJCAI-ECAI-2018, 2018
|Estrogenic activity data extraction and in silico prediction show the endocrine disruption potential of bisphenol a replacement compounds|
HW Ng, M Shu, H Luo, H Ye, W Ge, R Perkins, W Tong, H Hong
Chemical Research in Toxicology 28 (9), 1784-1795, 2015
|Competitive molecular docking approach for predicting estrogen receptor subtype α agonists and antagonists|
HW Ng, W Zhang, M Shu, H Luo, W Ge, R Perkins, W Tong, H Hong
BMC Bioinformatics 2014 (15(Suppl 11):S4), 2014
|Machine learning methods for predicting HLA-peptide binding activity|
H Luo, H Ye, HW Ng, L Shi, W Tong, D Mendrick, H Hong
Bioinformatics and Biology Insights 9 (S3), 21-29, 2015
|HLA-B*59:01: a marker for Stevens-Johnson syndrome/toxic epidermal necrolysis caused by methazolamide in Han Chinese|
F Yang, J Xuan, J Chen, H Zhong, H Luo, P Zhou, X Sun, L He, S Chen, ...
The Pharmacogenomics Journal 16, 83–87, 2016
|Predicting adverse drug reactions through interpretable deep learning framework|
S Dey, H Luo, A Fokoue, J Hu, P Zhang
BMC Bioinformatics 19 (Suppl 21), 476, 2018
|Development and validation of Decision Forest model for estrogen receptor binding prediction of chemicals using large data sets|
HW Ng, SW Doughty, H Luo, H Ye, W Ge, W Tong, H Hong
Chemical Research in Toxicology, 2015
|HLA-B*13:01 is associated with salazosulfapyridine-induced drug rash with eosinophilia and systemic symptoms in Chinese Han population|
F Yang, B Gu, L Zhang, J Xuan, H Luo, P Zhou, Q Zhu, S Yan, S Chen, ...
Pharmacogenomics 15 (11), 1461-1469, 2014
|Whole genome sequencing of 35 individuals provides insights into the genetic architecture of Korean population|
W Zhang, J Meehan, Z Su, HW Ng, M Shu, H Luo, W Ge, R Perkins, ...
BMC Bioinformatics 2014 (15(Suppl 11):S6), 2014
|Comparing genetic variants detected in the 1000 genomes project with SNPs determined by the International HapMap Consortium|
W Zhang, HW Ng, M Shu, H Luo, Z Su, W Ge, R Perkins, W Tong, H Hong
Journal of Genetics 94, 2015
|DPDR-CPI, a server that predicts drug positioning and drug repositioning via chemical-protein interactome|
H Luo, P Zhang, XH Cao, D Du, H Ye, H Huang, C Li, S Qin, C Wan, L Shi, ...
Scientific Reports 6, 35996, 2016