Deep generative models of genetic variation capture mutation effects

18 December 2017

Papers citing "Deep generative models of genetic variation capture mutation effects"

8 / 8 papers shown

Title
SFM-Protein: Integrative Co-evolutionary Pre-training for Advanced Protein Sequence Representation Liang He Peiran Jin Yaosen Min Shufang Xie Lijun Wu Tao Qin Xiaozhuan Liang Ran Bi Yuliang Jiang Tie-Yan Liu AI4TS 125 3 0 31 Oct 2024
RITA: a Study on Scaling Up Generative Protein Sequence Models Daniel Hesslow Niccoló Zanichelli Pascal Notin Iacopo Poli D. Marks 122 118 0 11 May 2022
Pre-training Co-evolutionary Protein Representation via A Pairwise Masked Language Model Liang He Shizhuo Zhang Lijun Wu Huanhuan Xia Fusong Ju ... Jianwei Zhu Pan Deng Jia Zhang Tao Qin Tie-Yan Liu 167 35 0 29 Oct 2021
AdaLead: A simple and robust adaptive greedy search algorithm for sequence design Sam Sinai Richard Wang Alexander Whatley Stewart Slocum Elina Locane Eric D. Kelsic 103 92 0 05 Oct 2020
A primer on model-guided exploration of fitness landscapes for biological sequence design Sam Sinai Eric D. Kelsic 150 31 0 04 Oct 2020
Learning Compositional Representations of Interacting Systems with Restricted Boltzmann Machines: Comparative Study of Lattice Proteins J. Tubiana Simona Cocco R. Monasson 91 28 0 18 Feb 2019
Deep Learning for Genomics: A Concise Overview Tianwei Yue Yuanxin Wang Longxiang Zhang Chunming Gu Haohan Wang Wenping Wang Qi Lyu Yujie Dun AILaw VLM BDL 193 94 0 02 Feb 2018
Variational auto-encoding of protein sequences Sam Sinai Eric D. Kelsic G. Church M. Nowak BDL DRL 114 70 0 09 Dec 2017