| scGNN is a novel graph neural network framework for single-cell RNA-Seq analyses J Wang, A Ma, Y Chang, J Gong, Y Jiang, R Qi, C Wang, H Fu, Q Ma, ... Nature Communications 12 (1), 1-11, 2021 | 536 | 2021 |
| QUBIC: a qualitative biclustering algorithm for analyses of gene expression data G Li, Q Ma, H Tang, AH Paterson, Y Xu Nucleic acids research 37 (15), e101-e101, 2009 | 339 | 2009 |
| Interpretation of differential gene expression results of RNA-seq data: review and integration A McDermaid, B Monier, J Zhao, B Liu, Q Ma Briefings in bioinformatics 20 (6), 2044-2054, 2019 | 299 | 2019 |
| Improving protein-protein interactions prediction accuracy using XGBoost feature selection and stacked ensemble classifier C Chen, Q Zhang, B Yu, Z Yu, PJ Lawrence, Q Ma, Y Zhang Computers in biology and medicine 123, 103899, 2020 | 253* | 2020 |
| LightGBM-PPI: Predicting protein-protein interactions through LightGBM with multi-information fusion C Chen, Q Zhang, Q Ma, B Yu Chemometrics and Intelligent Laboratory Systems 191, 54-64, 2019 | 239 | 2019 |
| DOOR 2.0: presenting operons and their functions through dynamic and integrated views X Mao, Q Ma, C Zhou, X Chen, H Zhang, J Yang, F Mao, W Lai, Y Xu Nucleic acids research 42 (D1), D654-D659, 2014 | 202 | 2014 |
| Predicting drug-target interactions using Lasso with random forest based on evolutionary information and chemical structure H Shi, S Liu, J Chen, X Li, Q Ma, B Yu Genomics 111 (6), 1839-1852, 2019 | 196 | 2019 |
| Integrative methods and practical challenges for single-cell multi-omics A Ma, A McDermaid, J Xu, Y Chang, Q Ma Trends in biotechnology 38 (9), 1007-1022, 2020 | 194 | 2020 |
| Clustering and classification methods for single-cell RNA-sequencing data R Qi, A Ma, Q Ma, Q Zou Briefings in bioinformatics 21 (4), 1196-1208, 2020 | 185 | 2020 |
| SubMito-XGBoost: predicting protein submitochondrial localization by fusing multiple feature information and eXtreme gradient boosting B Yu, W Qiu, C Chen, A Ma, J Jiang, H Zhou, Q Ma Bioinformatics 36 (4), 1074-1081, 2020 | 162 | 2020 |
| LncFinder: an integrated platform for long non-coding RNA identification utilizing sequence intrinsic composition, structural information and physicochemical property S Han, Y Liang, Q Ma, Y Xu, Y Zhang, W Du, C Wang, Y Li Briefings in bioinformatics 20 (6), 2009-2027, 2019 | 154* | 2019 |
| A shared disease-associated oligodendrocyte signature among multiple CNS pathologies M Kenigsbuch, P Bost, S Halevi, Y Chang, S Chen, Q Ma, R Hajbi, ... Nature neuroscience 25 (7), 876-886, 2022 | 153 | 2022 |
| Protein–protein interaction sites prediction by ensemble random forests with synthetic minority oversampling technique X Wang, B Yu, A Ma, C Chen, B Liu, Q Ma Bioinformatics, 2019 | 149 | 2019 |
| QUBIC2: a novel and robust biclustering algorithm for analyses and interpretation of large-scale RNA-Seq data J Xie, A Ma, Y Zhang, B Liu, S Cao, C Wang, J Xu, C Zhang, Q Ma Bioinformatics 36 (4), 1143-1149, 2020 | 136* | 2020 |
| Androgen conspires with the CD8+ T cell exhaustion program and contributes to sex bias in cancer H Kwon, JM Schafer, NJ Song, S Kaneko, A Li, T Xiao, A Ma, C Allen, ... Science immunology 7 (73), eabq2630, 2022 | 129 | 2022 |
| Caldicellulosiruptor core and pan genomes reveal determinants for non-cellulosomal thermophilic deconstruction of plant biomass SE Blumer-Schuette, RJ Giannone, JV Zurawski, I Ozdemir, Q Ma, Y Yin, ... Journal of Bacteriology, 2012 | 127 | 2012 |
| Microglia coordinate cellular interactions during spinal cord repair in mice FH Brennan, Y Li, C Wang, A Ma, Q Guo, Y Li, N Pukos, WA Campbell, ... Nature communications 13 (1), 4096, 2022 | 119 | 2022 |
| Metabolomics and multi-omics integration: a survey of computational methods and resources T Eicher, G Kinnebrew, A Patt, K Spencer, K Ying, Q Ma, R Machiraju, ... Metabolites 10 (5), 202, 2020 | 110 | 2020 |
| Prediction of protein–protein interactions based on elastic net and deep forest B Yu, C Chen, X Wang, Z Yu, A Ma, B Liu Expert Systems with Applications 176, 114876, 2021 | 109* | 2021 |
| A graph neural network model to estimate cell-wise metabolic flux using single cell RNA-seq data N Alghamdi, W Chang, P Dang, X Lu, C Wan, S Gampala, Z Huang, ... Genome Research 31 (1867–1884), 2020.09. 23.310656, 2021 | 107 | 2021 |
Anjun MaOhio State UniversityVerified email at osumc.edu
