TopologyNet: Topology based deep convolutional and multi-task neural networks for biomolecular property predictions Z Cang, GW Wei PLoS computational biology 13 (7), e1005690, 2017 | 329 | 2017 |
Inferring spatial and signaling relationships between cells from single cell transcriptomic data Z Cang, Q Nie Nature communications 11 (1), 1-13, 2020 | 282 | 2020 |
Representability of algebraic topology for biomolecules in machine learning based scoring and virtual screening Z Cang, L Mu, GW Wei PLoS computational biology 14 (1), e1005929, 2018 | 235 | 2018 |
Integration of element specific persistent homology and machine learning for protein‐ligand binding affinity prediction Z Cang, GW Wei International journal for numerical methods in biomedical engineering 34 (2 …, 2018 | 179 | 2018 |
Defining epidermal basal cell states during skin homeostasis and wound healing using single-cell transcriptomics D Haensel, S Jin, P Sun, R Cinco, M Dragan, Q Nguyen, Z Cang, Y Gong, ... Cell reports 30 (11), 3932-3947. e6, 2020 | 173 | 2020 |
A topology-based network tree for the prediction of protein–protein binding affinity changes following mutation M Wang, Z Cang, GW Wei Nature Machine Intelligence 2 (2), 116-123, 2020 | 157 | 2020 |
Mathematical deep learning for pose and binding affinity prediction and ranking in D3R Grand Challenges DD Nguyen, Z Cang, K Wu, M Wang, Y Cao, GW Wei Journal of computer-aided molecular design 33 (1), 71-82, 2019 | 155 | 2019 |
The landscape of cell–cell communication through single-cell transcriptomics AA Almet, Z Cang, S Jin, Q Nie Current opinion in systems biology 26, 12-23, 2021 | 145 | 2021 |
Screening cell–cell communication in spatial transcriptomics via collective optimal transport Z Cang, Y Zhao, AA Almet, A Stabell, R Ramos, MV Plikus, SX Atwood, ... Nature Methods, 1-11, 2023 | 139 | 2023 |
A topological approach for protein classification Z Cang, L Mu, K Wu, K Opron, K Xia, GW Wei Computational and Mathematical Biophysics 3 (1), 2015 | 130 | 2015 |
Analysis and prediction of protein folding energy changes upon mutation by element specific persistent homology Z Cang, GW Wei Bioinformatics 33 (22), 3549-3557, 2017 | 107 | 2017 |
A review of mathematical representations of biomolecular data DD Nguyen, Z Cang, GW Wei Physical Chemistry Chemical Physics 22 (8), 4343-4367, 2020 | 91 | 2020 |
Identifying multicellular spatiotemporal organization of cells with SpaceFlow H Ren, BL Walker, Z Cang, Q Nie Nature Communications 13 (1), 1-14, 2022 | 66 | 2022 |
Deciphering tissue structure and function using spatial transcriptomics BL Walker, Z Cang, H Ren, E Bourgain-Chang, Q Nie Communications Biology 5 (1), 1-10, 2022 | 65 | 2022 |
Systems and methods for drug design and discovery comprising applications of machine learning with differential geometric modeling G Wei, D Nguyen, Z Cang US Patent App. 17/043,551, 2021 | 35* | 2021 |
DEEPsc: a deep learning-based map connecting single-cell transcriptomics and spatial imaging data F Maseda, Z Cang, Q Nie Frontiers in Genetics 12, 636743, 2021 | 31 | 2021 |
Protein pocket detection via convex hull surface evolution and associated Reeb graph R Zhao, Z Cang, Y Tong, GW Wei Bioinformatics 34 (17), i830-i837, 2018 | 29 | 2018 |
Single-cell transcriptomic analysis of zebrafish cranial neural crest reveals spatiotemporal regulation of lineage decisions during development D Tatarakis, Z Cang, X Wu, PP Sharma, M Karikomi, AL MacLean, Q Nie, ... Cell Reports 37 (12), 110140, 2021 | 28 | 2021 |
Structural cavities are critical to balancing stability and activity of a membrane-integral enzyme R Guo, Z Cang, J Yao, M Kim, E Deans, G Wei, S Kang, H Hong Proceedings of the National Academy of Sciences 117 (36), 22146-22156, 2020 | 25 | 2020 |
A multiscale model via single-cell transcriptomics reveals robust patterning mechanisms during early mammalian embryo development Z Cang, Y Wang, Q Wang, KWY Cho, W Holmes, Q Nie PLoS computational biology 17 (3), e1008571, 2021 | 22 | 2021 |