| Deep-learning approach to identifying cancer subtypes using high-dimensional genomic data R Chen, L Yang, S Goodison, Y Sun Bioinformatics 36 (5), 1476-1483, 2020 | 100 | 2020 |
| SENSE: Siamese neural network for sequence embedding and alignment-free comparison W Zheng, L Yang, RJ Genco, J Wactawski-Wende, M Buck, Y Sun Bioinformatics 35 (11), 1820-1828, 2019 | 42 | 2019 |
| A modified clustering method based on self-organizing maps and its applications L Yang, Z Ouyang, Y Shi Procedia Computer Science 9, 1371-1379, 2012 | 39 | 2012 |
| SimplePPT: A simple principal tree algorithm Q Mao, L Yang, L Wang, S Goodison, Y Sun Proceedings of the 2015 SIAM International Conference on Data Mining, 792-800, 2015 | 33 | 2015 |
| Computational approach for deriving cancer progression roadmaps from static sample data Y Sun, J Yao, L Yang, R Chen, NJ Nowak, S Goodison Nucleic acids research 45 (9), e69-e69, 2017 | 23 | 2017 |
| An efficient and effective method to identify significantly perturbed subnetworks in cancer L Yang, R Chen, S Goodison, Y Sun Nature computational science 1 (1), 79-88, 2021 | 12 | 2021 |
| A multimodal framework for unsupervised feature fusion X Li, J Gao, H Li, L Yang, RK Srihari Proceedings of the 22nd ACM international conference on information …, 2013 | 6 | 2013 |
| Alignment-free comparison of metagenomics sequences via approximate string matching J Chen, L Yang, L Li, S Goodison, Y Sun Bioinformatics Advances 2 (1), vbac077, 2022 | 2 | 2022 |
| Predicting alignment distances via continuous sequence matching J Chen, LL Le Yang, Y Sun bioRxiv, 2020 | 2 | 2020 |
| Identifying Significantly Perturbed Subnetworks in Cancer Using Multiple Protein–Protein Interaction Networks L Yang, R Chen, T Melendy, S Goodison, Y Sun Cancers 15 (16), 4090, 2023 | | 2023 |
Yijun SunProfessor of Bioinformatics, State University of New York at BuffaloVerified email at buffalo.edu
