| Interactome INSIDER: a structural interactome browser for genomic studies MJ Meyer, JF Beltrán, S Liang, R Fragoza, A Rumack, J Liang, X Wei, ... Nature methods 15 (2), 107-114, 2018 | 145 | 2018 |
| SAAMBE-3D: predicting effect of mutations on protein–protein interactions S Pahari, G Li, AK Murthy, S Liang, R Fragoza, H Yu, E Alexov International journal of molecular sciences 21 (7), 2563, 2020 | 76 | 2020 |
| Extensive disruption of protein interactions by genetic variants across the allele frequency spectrum in human populations R Fragoza, J Das, SD Wierbowski, J Liang, TN Tran, S Liang, JF Beltran, ... Nature communications 10 (1), 4141, 2019 | 56 | 2019 |
| Leveraging genetic interaction for adverse drug-drug interaction prediction S Qian, S Liang, H Yu PLoS computational biology 15 (5), e1007068, 2019 | 26 | 2019 |
| A 3D structural SARS-CoV-2–human interactome to explore genetic and drug perturbations SD Wierbowski, S Liang, Y Liu, Y Chen, S Gupta, NM Andre, SM Lipkin, ... Nature methods 18 (12), 1477-1488, 2021 | 23 | 2021 |
| SAAMBE-SEQ: a sequence-based method for predicting mutation effect on protein–protein binding affinity G Li, S Pahari, AK Murthy, S Liang, R Fragoza, H Yu, E Alexov Bioinformatics 37 (7), 992-999, 2021 | 22 | 2021 |
| Deep learning methods for 3D structural proteome and interactome modeling D Lee, D Xiong, S Wierbowski, L Li, S Liang, H Yu Current opinion in structural biology 73, 102329, 2022 | 19 | 2022 |
| Revealing new therapeutic opportunities through drug target prediction: a class imbalance-tolerant machine learning approach S Liang, H Yu Bioinformatics 36 (16), 4490-4497, 2020 | 12 | 2020 |
| iRegNet3D: three-dimensional integrated regulatory network for the genomic analysis of coding and non-coding disease mutations S Liang, ND Tippens, Y Zhou, M Mort, PD Stenson, DN Cooper, H Yu Genome biology 18, 1-16, 2017 | 10 | 2017 |
| PIVOTAL: Prioritizing variants of uncertain significance with spatial genomic patterns in the 3D proteome S Liang, M Mort, PD Stenson, DN Cooper, H Yu bioRxiv, 2020.06. 04.135103, 2020 | 5 | 2020 |
| Extracting complementary insights from molecular phenotypes for prioritization of disease-associated mutations SD Wierbowski, R Fragoza, S Liang, H Yu Current opinion in systems biology 11, 107-116, 2018 | 5 | 2018 |
| Structurally-informed human interactome reveals proteome-wide perturbations by disease mutations D Xiong, Y Qiu, J Zhao, Y Zhou, D Lee, S Gupta, M Torres, W Lu, S Liang, ... bioRxiv, 2023 | 1 | 2023 |
Haiyuan YuProfessor, Cornell UniversityVerified email at cornell.edu
