| 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), 1882, 2021 | 544 | 2021 |
| 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 | 142 | 2019 |
| 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 | 134 | 2022 |
| scREAD: a single-cell RNA-Seq database for Alzheimer's disease J Jiang, C Wang, R Qi, H Fu, Q Ma Iscience 23 (11), 2020 | 100 | 2020 |
| Single-cell biological network inference using a heterogeneous graph transformer A Ma, X Wang, J Li, C Wang, T Xiao, Y Liu, H Cheng, J Wang, Y Li, ... Nature Communications 14 (1), 964, 2023 | 92 | 2023 |
| NIH SenNet Consortium to map senescent cells throughout the human lifespan to understand physiological health Brown University TDA Wang Siyuan (Steven) 34, ... Nature aging 2 (12), 1090-1100, 2022 | 79 | 2022 |
| 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 | 69 | 2020 |
| Prediction of regulatory motifs from human Chip-sequencing data using a deep learning framework J Yang, A Ma, AD Hoppe, C Wang, Y Li, C Zhang, Y Wang, B Liu, Q Ma Nucleic acids research 47 (15), 7809-7824, 2019 | 69 | 2019 |
| Spatially resolved transcriptomics reveals genes associated with the vulnerability of middle temporal gyrus in Alzheimer’s disease S Chen, Y Chang, L Li, D Acosta, Y Li, Q Guo, C Wang, E Turkes, ... Acta Neuropathologica Communications 10 (1), 188, 2022 | 64 | 2022 |
| CirRNAPL: a web server for the identification of circRNA based on extreme learning machine M Niu, J Zhang, Y Li, C Wang, Z Liu, H Ding, Q Zou, Q Ma Computational and structural biotechnology journal 18, 834-842, 2020 | 46 | 2020 |
| IRIS3: integrated cell-type-specific regulon inference server from single-cell RNA-Seq A Ma, C Wang, Y Chang, FH Brennan, A McDermaid, B Liu, C Zhang, ... Nucleic acids research 48 (W1), W275-W286, 2020 | 41 | 2020 |
| Wolframin is a novel regulator of tau pathology and neurodegeneration S Chen, D Acosta, L Li, J Liang, Y Chang, C Wang, J Fitzgerald, ... Acta Neuropathologica 143 (5), 547-569, 2022 | 33 | 2022 |
| IRIS-EDA: An integrated RNA-Seq interpretation system for gene expression data analysis B Monier, A McDermaid, C Wang, J Zhao, A Miller, A Fennell, Q Ma PLoS computational biology 15 (2), e1006792, 2019 | 32 | 2019 |
| Using machine learning to measure relatedness between genes: a multi-features model Y Wang, S Yang, J Zhao, W Du, Y Liang, C Wang, F Zhou, Y Tian, Q Ma Scientific reports 9 (1), 4192, 2019 | 30 | 2019 |
| Impaired human cardiac cell development due to NOTCH1 deficiency S Ye, C Wang, Z Xu, H Lin, X Wan, Y Yu, S Adhicary, JZ Zhang, Y Zhou, ... Circulation research 132 (2), 187-204, 2023 | 27 | 2023 |
| A new machine learning-based framework for mapping uncertainty analysis in RNA-Seq read alignment and gene expression estimation A McDermaid, X Chen, Y Zhang, C Wang, S Gu, J Xie, Q Ma Frontiers in genetics 9, 313, 2018 | 26 | 2018 |
| Assessing deep learning methods in cis-regulatory motif finding based on genomic sequencing data S Zhang, A Ma, J Zhao, D Xu, Q Ma, Y Wang Briefings in Bioinformatics 23 (1), bbab374, 2022 | 22 | 2022 |
| A Single-cell and Spatial RNA-seq Database for Alzheimer’s Disease (ssREAD) C Wang, A Diana, M McNutt, J Bian, A Ma, H Fu, Q Ma bioRxiv, 2024 | 19* | 2024 |
| Biological aging of CNS-resident cells alters the clinical course and immunopathology of autoimmune demyelinating disease JR Atkinson, AD Jerome, AR Sas, A Munie, C Wang, A Ma, WD Arnold, ... JCI insight 7 (12), 2022 | 16 | 2022 |
| Deepmaps: Single-cell biological network inference using heterogeneous graph transformer A Ma, X Wang, C Wang, J Li, T Xiao, J Wang, Y Li, Y Liu, Y Chang, ... Biorxiv, 2021.10. 31.466658, 2021 | 13 | 2021 |
Qin MaProfessor, Department of Biomedical Informatics, The Ohio State UniversityE-mail megerősítve itt: osumc.edu