| Applications of machine learning in drug discovery and development J Vamathevan, D Clark, P Czodrowski, I Dunham, E Ferran, G Lee, B Li, ... Nature reviews Drug discovery 18 (6), 463-477, 2019 | 1420 | 2019 |
| Comparison of RNA-Seq and microarray in transcriptome profiling of activated T cells S Zhao, WP Fung-Leung, A Bittner, K Ngo, X Liu PloS one 9 (1), e78644, 2014 | 1191 | 2014 |
| Misuse of RPKM or TPM normalization when comparing across samples and sequencing protocols S Zhao, Z Ye, R Stanton Rna 26 (8), 903-909, 2020 | 205 | 2020 |
| Evaluation of two main RNA-seq approaches for gene quantification in clinical RNA sequencing: polyA+ selection versus rRNA depletion S Zhao, Y Zhang, R Gamini, B Zhang, D Von Schack Scientific reports 8 (1), 4781, 2018 | 199 | 2018 |
| Evaluation and comparison of computational tools for RNA-seq isoform quantification C Zhang, B Zhang, LL Lin, S Zhao BMC genomics 18 (1), 1-11, 2017 | 173 | 2017 |
| Subsets of ILC3− ILC1-like cells generate a diversity spectrum of innate lymphoid cells in human mucosal tissues M Cella, R Gamini, C Sécca, PL Collins, S Zhao, V Peng, ML Robinette, ... Nature immunology 20 (8), 980-991, 2019 | 153 | 2019 |
| A comprehensive evaluation of ensembl, RefSeq, and UCSC annotations in the context of RNA-seq read mapping and gene quantification S Zhao, B Zhang BMC genomics 16 (1), 1-14, 2015 | 146 | 2015 |
| RORγt and RORα signature genes in human Th17 cells G Castro, X Liu, K Ngo, A De Leon-Tabaldo, S Zhao, R Luna-Roman, J Yu, ... PloS one 12 (8), e0181868, 2017 | 135 | 2017 |
| Comparison of stranded and non-stranded RNA-seq transcriptome profiling and investigation of gene overlap S Zhao, Y Zhang, W Gordon, J Quan, H Xi, S Du, D von Schack, B Zhang BMC genomics 16 (1), 1-14, 2015 | 100 | 2015 |
| Single-cell analyses of Crohn’s disease tissues reveal intestinal intraepithelial T cells heterogeneity and altered subset distributions N Jaeger, R Gamini, M Cella, JL Schettini, M Bugatti, S Zhao, ... Nature communications 12 (1), 1921, 2021 | 80 | 2021 |
| Analysis of a data set of paired uncomplexed protein structures: new metrics for side‐chain flexibility and model evaluation S Zhao, DS Goodsell, AJ Olson Proteins: Structure, Function, and Bioinformatics 43 (3), 271-279, 2001 | 67 | 2001 |
| Rainbow: a tool for large-scale whole-genome sequencing data analysis using cloud computing S Zhao, K Prenger, L Smith, T Messina, H Fan, E Jaeger, S Stephens BMC genomics 14 (1), 1-11, 2013 | 62 | 2013 |
| Alternative splicing, RNA-seq and drug discovery S Zhao Drug discovery today 24 (6), 1258-1267, 2019 | 59 | 2019 |
| Standard machine learning approaches outperform deep representation learning on phenotype prediction from transcriptomics data AM Smith, JR Walsh, J Long, CB Davis, P Henstock, MR Hodge, ... BMC bioinformatics 21 (1), 1-18, 2020 | 50 | 2020 |
| Toll like receptor 3 antagonists, methods and uses JM Carton, S Chen, M Cunningham, A Das, K Duffy, JM Giles-Komar, ... US Patent 8,153,583, 2012 | 50 | 2012 |
| Human framework adaptation of a mouse anti-human IL-13 antibody J Fransson, A Teplyakov, G Raghunathan, E Chi, W Cordier, T Dinh, ... Journal of molecular biology 398 (2), 214-231, 2010 | 45 | 2010 |
| QuickRNASeq lifts large-scale RNA-seq data analyses to the next level of automation and interactive visualization S Zhao, L Xi, J Quan, H Xi, Y Zhang, D von Schack, M Vincent, B Zhang BMC genomics 17 (1), 1-15, 2016 | 42 | 2016 |
| QuickMIRSeq: a pipeline for quick and accurate quantification of both known miRNAs and isomiRs by jointly processing multiple samples from microRNA sequencing S Zhao, W Gordon, S Du, C Zhang, W He, L Xi, S Mathur, M Agostino, ... BMC bioinformatics 18, 1-14, 2017 | 39 | 2017 |
| Union exon based approach for RNA-seq gene quantification: To be or not to be? S Zhao, L Xi, B Zhang PloS one 10 (11), e0141910, 2015 | 33 | 2015 |
| Assessment of the impact of using a reference transcriptome in mapping short RNA-Seq reads S Zhao PLoS One 9 (7), e101374, 2014 | 30 | 2014 |
