| PecanPy: a fast, efficient and parallelized Python implementation of node2vec R Liu, A Krishnan Bioinformatics 37 (19), 3377-3379, 2021 | 58 | 2021 |
| Supervised learning is an accurate method for network-based gene classification R Liu, CA Mancuso, A Yannakopoulos, KA Johnson, A Krishnan Bioinformatics 36 (11), 3457-3465, 2020 | 49 | 2020 |
| Deep learning in single-cell analysis D Molho, J Ding, W Tang, Z Li, H Wen, Y Wang, J Venegas, W Jin, R Liu, ... ACM Transactions on Intelligent Systems and Technology 15 (3), 1-62, 2024 | 27 | 2024 |
| Accurately modeling biased random walks on weighted networks using node2vec+ R Liu, M Hirn, A Krishnan Bioinformatics 39 (1), btad047, 2023 | 27 | 2023 |
| Taxonomy of benchmarks in graph representation learning R Liu, S Cantürk, F Wenkel, S McGuire, X Wang, A Little, L O’Bray, ... Learning on Graphs Conference, 6: 1-6: 25, 2022 | 17 | 2022 |
| Graph positional and structural encoder S Cantürk, R Liu, O Lapointe-Gagné, V Létourneau, G Wolf, D Beaini, ... arXiv preprint arXiv:2307.07107, 2023 | 14 | 2023 |
| Single-cell multimodal prediction via transformers W Tang, H Wen, R Liu, J Ding, W Jin, Y Xie, H Liu, J Tang Proceedings of the 32nd ACM International Conference on Information and …, 2023 | 13 | 2023 |
| Dance: A deep learning library and benchmark for single-cell analysis J Ding, H Wen, W Tang, R Liu, Z Li, J Venegas, R Su, D Molho, W Jin, ... bioRxiv, 2022.10. 19.512741, 2022 | 10 | 2022 |
| Applications of an Association Activity Coefficient Model, NRTL-PA, to Alcohol-Containing Mixtures AM Bala, R Liu, L Peereboom, CT Lira Industrial & Engineering Chemistry Research 61 (42), 15603-15619, 2022 | 10 | 2022 |
| Single cells are spatial tokens: Transformers for spatial transcriptomic data imputation H Wen, W Tang, W Jin, J Ding, R Liu, X Dai, F Shi, L Shang, H Liu, Y Xie arXiv preprint arXiv:2302.03038, 2023 | 9 | 2023 |
| GenePlexus: a web-server for gene discovery using network-based machine learning CA Mancuso, PS Bills, D Krum, J Newsted, R Liu, A Krishnan Nucleic Acids Research 50 (W1), W358-W366, 2022 | 9 | 2022 |
| DANCE: A deep learning library and benchmark platform for single-cell analysis J Ding, R Liu, H Wen, W Tang, Z Li, J Venegas, R Su, D Molho, W Jin, ... Genome Biology 25 (1), 72, 2024 | 8 | 2024 |
| PyGenePlexus: a Python package for gene discovery using network-based machine learning CA Mancuso, R Liu, A Krishnan Bioinformatics 39 (2), btad064, 2023 | 8 | 2023 |
| Accurately modeling biased random walks on weighted graphs using Node2vec+ R Liu, M Hirn, A Krishnan arXiv preprint arXiv:2109.08031, 2021 | 8 | 2021 |
| SpatialCTD: A Large-Scale Tumor Microenvironment Spatial Transcriptomic Dataset to Evaluate Cell Type Deconvolution for Immuno-Oncology J Ding, L Li, Q Lu, J Venegas, Y Wang, L Wu, W Jin, H Wen, R Liu, ... Journal of Computational Biology 31 (9), 871-885, 2024 | 4 | 2024 |
| Joint representation of molecular networks from multiple species improves gene classification CA Mancuso, KA Johnson, R Liu, A Krishnan PLOS Computational Biology 20 (1), e1011773, 2024 | 4 | 2024 |
| A general single-cell analysis framework via conditional diffusion generative models W Tang, R Liu, H Wen, X Dai, J Ding, H Li, W Fan, Y Xie, J Tang bioRxiv, 2023.10. 13.562243, 2023 | 4 | 2023 |
| Open Biomedical Network Benchmark A Python Toolkit for Benchmarking Datasets with Biomedical Networks R Liu, A Krishnan bioRxiv, 2023.01. 10.523485, 2023 | 3 | 2023 |
| CONE: COntext-specific Network Embedding via Contextualized Graph Attention R Liu, H Yuan, KA Johnson, A Krishnan bioRxiv, 2023.10. 21.563390, 2023 | 2 | 2023 |
| Towards a taxonomy of graph learning datasets R Liu, S Cantürk, F Wenkel, D Sandfelder, D Kreuzer, A Little, S McGuire, ... arXiv preprint arXiv:2110.14809, 2021 | 2 | 2021 |
Arjun KrishnanAssociate Professor, Biomedical Informatics, University of Colorado Anschutz Medical CampusZweryfikowany adres z cuanschutz.edu