| Coarse-grained residue-based models of disordered protein condensates: utility and limitations of simple charge pattern parameters S Das, AN Amin, YH Lin, HS Chan Physical Chemistry Chemical Physics 20 (45), 28558-28574, 2018 | 121 | 2018 |
| Controlled release strategy designed for intravitreal protein delivery to the retina V Delplace, A Ortin-Martinez, ELS Tsai, AN Amin, V Wallace, MS Shoichet Journal of Controlled Release 293, 10-20, 2019 | 65 | 2019 |
| Analytical theory for sequence-specific binary fuzzy complexes of charged intrinsically disordered proteins AN Amin, YH Lin, S Das, HS Chan The Journal of Physical Chemistry B 124 (31), 6709-6720, 2020 | 43 | 2020 |
| Non-identifiability and the blessings of misspecification in models of molecular fitness E Weinstein, A Amin, J Frazer, D Marks Advances in neural information processing systems 35, 5484-5497, 2022 | 23 | 2022 |
| Optimal design of stochastic DNA synthesis protocols based on generative sequence models EN Weinstein, AN Amin, WS Grathwohl, D Kassler, J Disset, D Marks International Conference on Artificial Intelligence and Statistics, 7450-7482, 2022 | 23 | 2022 |
| A generative nonparametric Bayesian model for whole genomes A Amin, EN Weinstein, D Marks Advances in Neural Information Processing Systems 34, 27798-27812, 2021 | 12 | 2021 |
| A kernelized Stein discrepancy for biological sequences AN Amin, EN Weinstein, DS Marks International Conference on Machine Learning, 718-767, 2023 | 4 | 2023 |
| Biological sequence kernels with guaranteed flexibility AN Amin, EN Weinstein, DS Marks arXiv preprint arXiv:2304.03775, 2023 | 4 | 2023 |
| Manufacturing-aware generative model architectures enable biological sequence design and synthesis at Petascale EN Weinstein, MG Gollub, A Slabodkin, CL Gardner, K Dobbs, XB Cui, ... bioRxiv, 2024.09. 13.612900, 2024 | 3 | 2024 |
| Nonparametric Methods for Building and Evaluating Models of Biological Sequences AN Amin Harvard University, 2023 | 1 | 2023 |
| Bayesian Optimization of Antibodies Informed by a Generative Model of Evolving Sequences AN Amin, N Gruver, Y Kuang, L Li, H Elliott, C McCarter, A Raghu, ... arXiv preprint arXiv:2412.07763, 2024 | | 2024 |
| Scalable and Flexible Causal Discovery with an Efficient Test for Adjacency AN Amin, AG Wilson arXiv preprint arXiv:2406.09177, 2024 | | 2024 |
| Kernel-Based Evaluation of Conditional Biological Sequence Models P Glaser, S Paul, AM Hummer, C Deane, DS Marks, AN Amin Forty-first International Conference on Machine Learning, 2024 | | 2024 |
| Theory for a Sequence-Specific “Fuzzy” Binding Mechanism Between a Pair of Intrinsically Disordered Proteins AN Amin, YH Lin, S Das, HS Chan arXiv preprint arXiv:1910.11194, 2019 | | 2019 |
| Theoretical Perspectives on Cellular Compartmentalization by Phase Separation YH Lin, S Das, A Amin, A Eisen, J Forman-Kay, HS Chan APS March Meeting Abstracts 2019, V54. 001, 2019 | | 2019 |
| Cluster-expansion theory for sequence-specific''fuzzy''interaction between a pair of intrinsically disordered proteins A Amin, YH Lin, S Das, HS Chan APS March Meeting Abstracts 2019, Y64. 004, 2019 | | 2019 |
| Bringing furan/maleimide Diels-Alder HA hydrogel chemistry to physiological conditions, for biomedical applications V Delplace, A Amin, M Shoichet ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY 255, 2018 | | 2018 |
| Kernelized Stein Discrepancies for Biological Sequences AN Amin, EN Weinstein, DS Marks NeurIPS 2022 Workshop on Learning Meaningful Representations of Life, 0 | | |
| Designing Proteins using Sparse Data A Shaw, JE Shin, NN Thadani, AN Amin, DS Marks NeurIPS 2022 Workshop on Learning Meaningful Representations of Life, 0 | | |
