MHCflurry: open-source class I MHC binding affinity prediction TJ O'Donnell, A Rubinsteyn, M Bonsack, AB Riemer, U Laserson, ... Cell systems 7 (1), 129-132. e4, 2018 | 375 | 2018 |
MHCflurry 2.0: improved pan-allele prediction of MHC class I-presented peptides by incorporating antigen processing TJ O’Donnell, A Rubinsteyn, U Laserson Cell systems 11 (1), 42-48. e7, 2020 | 268 | 2020 |
Defining HLA-II ligand processing and binding rules with mass spectrometry enhances cancer epitope prediction JG Abelin, D Harjanto, M Malloy, P Suri, T Colson, SP Goulding, ... Immunity 51 (4), 766-779. e17, 2019 | 205 | 2019 |
Somatic mutations and neoepitope homology in melanomas treated with CTLA-4 blockade T Nathanson, A Ahuja, A Rubinsteyn, BA Aksoy, MD Hellmann, D Miao, ... Cancer immunology research 5 (1), 84-91, 2017 | 140 | 2017 |
Using a machine learning approach to predict outcomes after radiosurgery for cerebral arteriovenous malformations EK Oermann, A Rubinsteyn, D Ding, J Mascitelli, RM Starke, JB Bederson, ... Scientific reports 6 (1), 21161, 2016 | 108 | 2016 |
Computational pipeline for the PGV-001 neoantigen vaccine trial A Rubinsteyn, J Kodysh, I Hodes, S Mondet, BA Aksoy, JP Finnigan, ... Frontiers in immunology 8, 1807, 2018 | 58 | 2018 |
Parakeet: A Just-In-Time Parallel Accelerator for Python A Rubinsteyn, N Weinman, E Hielscher, D Shasha HotPar 2012, 2012 | 53 | 2012 |
fancyimpute: An imputation library for python A Rubinsteyn, S Feldman URL https://github. com/iskandr/fancyimpute, 2016 | 47 | 2016 |
Landscape and selection of vaccine epitopes in SARS-CoV-2 CC Smith, KS Olsen, KM Gentry, M Sambade, W Beck, J Garness, ... Genome medicine 13 (1), 101, 2021 | 45 | 2021 |
Bioinformatic methods for cancer neoantigen prediction S Boegel, JC Castle, J Kodysh, T O'Donnell, A Rubinsteyn Progress in molecular biology and translational science 164, 25-60, 2019 | 29 | 2019 |
OpenVax: an open-source computational pipeline for cancer neoantigen prediction J Kodysh, A Rubinsteyn Bioinformatics for Cancer Immunotherapy: Methods and Protocols, 147-160, 2020 | 24 | 2020 |
scikit-cuda 0.5. 1: a Python interface to GPU-powered libraries. 2015. doi: 10.5281/zenodo. 40565 LE Givon, T Unterthiner, NB Erichson, DW Chiang, E Larson, L Pfister, ... Accessed, 2017 | 24* | 2017 |
Vaxrank: a computational tool for designing personalized cancer vaccines A Rubinsteyn, I Hodes, J Kodysh, J Hammerbacher Biorxiv, 142919, 2017 | 23 | 2017 |
Predicting peptide-MHC binding affinities with imputed training data A Rubinsteyn, T O'Donnell, N Damaraju, J Hammerbacher bioRxiv, 054775, 2016 | 22 | 2016 |
Learning random forests on the GPU Y Liao, A Rubinsteyn, R Power, J Li NIPS workshop on parallel and large-scale machine learning (Big Learning), 2013 | 22 | 2013 |
Recognizing currency bills using a mobile phone: an assistive aid for the visually impaired N Paisios, A Rubinsteyn, V Vyas, L Subramanian Proceedings of the 24th annual ACM symposium adjunct on User interface …, 2011 | 19 | 2011 |
MHCflurry 2.0: improved pan-allele prediction of MHC class I-presented peptides by incorporating antigen processing. Cell Syst 11: 42–48. e7 TJ O’Donnell, A Rubinsteyn, U Laserson P42-P48. e7, 2020 | 17 | 2020 |
Mutation-derived tumor antigens: novel targets in cancer immunotherapy JP Finnigan Jr, A Rubinsteyn, J Hammerbacher, N Bhardwaj Oncology 29 (12), 970-970, 2015 | 17 | 2015 |
Somatic mutations and neoepitope homology in melanomas treated with CTLA-4 blockade. Cancer Immunol. Res. 2017; 5: 84–91. doi: 10.1158/2326-6066 T Nathanson, A Ahuja, A Rubinsteyn, BA Aksoy, MD Hellmann, D Miao, ... CIR-16-0019.[Europe PMC free article][Abstract][CrossRef][Google Scholar], 0 | 17 | |
Exchanging cash with no fear: A fast mobile money reader for the blind N Paisios, A Rubinsteyn, L Subramanian Workshop on Frontiers in Accessibility for Pervasive Computing. ACM, 2012 | 16 | 2012 |