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Kevin K. Yang
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2020 – today
- 2023
- [j7]Ava P. Amini, Kevin K. Yang
:
From noise to protein with image models. Nat. Comput. Sci. 3(5): 366-367 (2023) - [j6]Carolina Rios-Martinez, Nicholas Bhattacharya, Ava P. Amini
, Lorin Crawford
, Kevin K. Yang
:
Deep self-supervised learning for biosynthetic gene cluster detection and product classification. PLoS Comput. Biol. 19(5) (2023) - 2022
- [j5]Samuel Goldman
, Ria Das, Kevin K. Yang
, Connor W. Coley
:
Machine learning modeling of family wide enzyme-substrate specificity screens. PLoS Comput. Biol. 18(2) (2022) - [j4]Wai-Shing Tang
, Gabriel Monteiro da Silva
, Henry Kirveslahti
, Erin Skeens
, Bibo Feng, Timothy Sudijono
, Kevin K. Yang
, Sayan Mukherjee
, Brenda M. Rubenstein
, Lorin Crawford
:
A topological data analytic approach for discovering biophysical signatures in protein dynamics. PLoS Comput. Biol. 18(5) (2022) - [i6]Mingyang Hu, Fajie Yuan, Kevin K. Yang, Fusong Ju, Jin Su, Hui Wang, Fei Yang, Qiuyang Ding:
Exploring evolution-based & -free protein language models as protein function predictors. CoRR abs/2206.06583 (2022) - [i5]Kevin E. Wu, Kevin K. Yang, Rianne van den Berg, James Y. Zou, Alex X. Lu, Ava P. Amini:
Protein structure generation via folding diffusion. CoRR abs/2209.15611 (2022) - 2021
- [c2]Christian Dallago, Jody Mou, Kadina E. Johnston, Bruce J. Wittmann, Nicholas Bhattacharya, Samuel Goldman, Ali Madani, Kevin K. Yang:
FLIP: Benchmark tasks in fitness landscape inference for proteins. NeurIPS Datasets and Benchmarks 2021 - [i4]Zachary Wu, Kadina E. Johnston, Frances H. Arnold, Kevin K. Yang:
Protein sequence design with deep generative models. CoRR abs/2104.04457 (2021) - [i3]Brian L. Hie, Kevin K. Yang:
Adaptive machine learning for protein engineering. CoRR abs/2106.05466 (2021) - [i2]Samuel Goldman, Ria Das, Kevin K. Yang, Connor W. Coley:
Machine learning modeling of family wide enzyme-substrate specificity screens. CoRR abs/2109.03900 (2021)
2010 – 2019
- 2019
- [c1]Kevin K. Yang, Yuxin Chen, Alycia Lee, Yisong Yue:
Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design. AISTATS 2019: 3410-3419 - [i1]Kevin K. Yang, Yuxin Chen, Alycia Lee, Yisong Yue:
Batched Stochastic Bayesian Optimization via Combinatorial Constraints Design. CoRR abs/1904.08102 (2019) - 2018
- [j3]Kevin K. Yang
, Zachary Wu, Claire N. Bedbrook
, Frances H. Arnold
:
Learned protein embeddings for machine learning. Bioinform. 34(15): 2642-2648 (2018) - [j2]Kevin K. Yang
, Zachary Wu, Claire N. Bedbrook
, Frances H. Arnold:
Learned protein embeddings for machine learning. Bioinform. 34(23): 4138 (2018) - 2017
- [j1]Claire N. Bedbrook
, Kevin K. Yang
, Austin J. Rice, Viviana Gradinaru, Frances H. Arnold
:
Machine learning to design integral membrane channelrhodopsins for efficient eukaryotic expression and plasma membrane localization. PLoS Comput. Biol. 13(10) (2017)
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