Worldwide Frequencies of APOL1 Renal Risk Variants GN Nadkarni, CR Gignoux, EP Sorokin, M Daya, R Rahman, KC Barnes, ... New England Journal of Medicine 379 (26), 2571-2572, 2018 | 89 | 2018 |
Redefining the protein kinase conformational space with machine learning PMU Ung, R Rahman, A Schlessinger Cell chemical biology 25 (7), 916-924. e2, 2018 | 82 | 2018 |
Bow-tie signaling in c-di-GMP: Machine learning in a simple biochemical network J Yan, M Deforet, KE Boyle, R Rahman, R Liang, C Okegbe, LEP Dietrich, ... PLoS computational biology 13 (8), e1005677, 2017 | 48 | 2017 |
Association of autism spectrum disorder with prenatal exposure to medication affecting neurotransmitter systems M Janecka, A Kodesh, SZ Levine, SI Lusskin, A Viktorin, R Rahman, ... Jama Psychiatry 75 (12), 1217-1224, 2018 | 38 | 2018 |
Identification of newborns at risk for autism using electronic medical records and machine learning R Rahman, A Kodesh, SZ Levine, S Sandin, A Reichenberg, ... European Psychiatry 63 (1), e22, 2020 | 33 | 2020 |
Transcriptomic profiling of human cardiac cells predicts protein kinase inhibitor-associated cardiotoxicity JGC van Hasselt, R Rahman, J Hansen, A Stern, JV Shim, Y Xiong, ... Nature Communications 11 (1), 4809, 2020 | 31 | 2020 |
KinaMetrix: a web resource to investigate kinase conformations and inhibitor space R Rahman, PMU Ung, A Schlessinger Nucleic acids research 47 (D1), D361-D366, 2019 | 29 | 2019 |
Systems-level analysis of NalD mutation, a recurrent driver of rapid drug resistance in acute Pseudomonas aeruginosa infection J Yan, H Estanbouli, C Liao, W Kim, JM Monk, R Rahman, M Kamboj, ... PLoS computational biology 15 (12), e1007562, 2019 | 14 | 2019 |
Maternal health around pregnancy and autism risk: a diagnosis-wide, population-based study A Kodesh, SZ Levine, V Khachadourian, R Rahman, A Schlessinger, ... Psychological medicine 52 (16), 4076-4084, 2022 | 12 | 2022 |
Protein structure–based gene expression signatures R Rahman, N Zatorski, J Hansen, Y Xiong, JGC van Hasselt, EA Sobie, ... Proceedings of the National Academy of Sciences 118 (19), e2014866118, 2021 | 10 | 2021 |
Generation of G protein-coupled receptor antibodies differentially sensitive to conformational states AS Heimann, A Gupta, I Gomes, R Rayees, A Schlessinger, ES Ferro, ... PLoS One 12 (11), e0187306, 2017 | 10 | 2017 |
Investigating the conformational landscape of AlphaFold2-predicted protein kinase structures C Al-Masri, F Trozzi, SH Lin, O Tran, N Sahni, M Patek, A Cichonska, ... Bioinformatics Advances 3 (1), vbad129, 2023 | 5 | 2023 |
AI for targeted polypharmacology: The next frontier in drug discovery A Cichońska, B Ravikumar, R Rahman Current Opinion in Structural Biology 84, 102771, 2024 | 2 | 2024 |
Preference Optimization for Molecular Language Models R Park, R Theisen, N Sahni, M Patek, A Cichońska, R Rahman arXiv preprint arXiv:2310.12304, 2023 | 2 | 2023 |
Maternal health around pregnancy and autism risk: a population-based study A Kodesh, SZ Levine, V Khachadourian, R Rahman, A Schlessinger, ... medRxiv, 2020.05. 19.20089581, 2020 | 2 | 2020 |
Structural signatures: a web server for exploring a database of and generating protein structural features from human cell lines and tissues N Zatorski, D Stein, R Rahman, R Iyengar, A Schlessinger Database 2022, baac053, 2022 | 1 | 2022 |
Redefining the protein kinase conformational space with machine learning PMU Ung, R Rahman, A Schlessinger Biophysical Journal 116 (3), 58a-59a, 2019 | 1 | 2019 |
Leveraging multiple data types for improved compound-kinase bioactivity prediction R Theisen, T Wang, B Ravikumar, R Rahman, A Cichońska bioRxiv, 2024.03. 07.583951, 2024 | | 2024 |
Maternal Medications in Pregnancy and Risk of Autism in the Offspring V Khachadourian, N Zatorski, R Rahman, A Kodesh, S Levine, ... NEUROPSYCHOPHARMACOLOGY 46 (SUPPL 1), 133-133, 2021 | | 2021 |
Integrating Structure and Machine Learning to Characterize Drug Action R Rahman Icahn School of Medicine at Mount Sinai, 2020 | | 2020 |