Alex Rubinsteyn
Alex Rubinsteyn
University of North Carolina - Chapel Hill
Verified email at - Homepage
Cited by
Cited by
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
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
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
Somatic Mutations and Neoepitope Homology in Melanomas Treated with CTLA-4 BlockadeMutations and Neoepitopes in Melanoma
T Nathanson, A Ahuja, A Rubinsteyn, BA Aksoy, MD Hellmann, D Miao, ...
Cancer immunology research 5 (1), 84-91, 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
Parakeet: A Just-In-Time Parallel Accelerator for Python
A Rubinsteyn, N Weinman, E Hielscher, D Shasha
HotPar 2012, 2012
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
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
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
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
fancyimpute: An imputation library for python
A Rubinsteyn, S Feldman
URL https://github. com/iskandr/fancyimpute, 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
Vaxrank: a computational tool for designing personalized cancer vaccines
A Rubinsteyn, I Hodes, J Kodysh, J Hammerbacher
bioRxiv, 142919, 2017
Predicting peptide-MHC binding affinities with imputed training data
A Rubinsteyn, T O'Donnell, N Damaraju, J Hammerbacher
bioRxiv, 054775, 2016
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
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
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
OpenVax: an open-source computational pipeline for cancer neoantigen prediction
J Kodysh, A Rubinsteyn
Bioinformatics for Cancer Immunotherapy: Methods and Protocols, 147-160, 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
How fast can we make interpreted Python?
R Power, A Rubinsteyn
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