Learning protein sequence embeddings using information from structure

22 February 2019

Papers citing "Learning protein sequence embeddings using information from structure"

8 / 58 papers shown

Title
BERTology Meets Biology: Interpreting Attention in Protein Language Models Jesse Vig Ali Madani L. Varshney Caiming Xiong R. Socher Nazneen Rajani 29 288 0 26 Jun 2020
Enforcing Predictive Invariance across Structured Biomedical Domains Wengong Jin Regina Barzilay Tommi Jaakkola OOD 26 27 0 06 Jun 2020
Energy-based models for atomic-resolution protein conformations Yilun Du Joshua Meier Jerry Ma Rob Fergus Alexander Rives 20 56 0 27 Apr 2020
CogMol: Target-Specific and Selective Drug Design for COVID-19 Using Deep Generative Models Vijil Chenthamarakshan Payel Das Samuel C. Hoffman Hendrik Strobelt Inkit Padhi ... Benjamin Hoover Matteo Manica Jannis Born Teodoro Laino Aleksandra Mojsilović 37 41 0 02 Apr 2020
Embedding Comparator: Visualizing Differences in Global Structure and Local Neighborhoods via Small Multiples Angie Boggust Brandon Carter Arvind Satyanarayan 36 62 0 10 Dec 2019
Pre-Training of Deep Bidirectional Protein Sequence Representations with Structural Information Seonwoo Min Seunghyun Park Siwon Kim Hyun-Soo Choi Byunghan Lee Sungroh Yoon SSL 6 62 0 25 Nov 2019
Evaluating Protein Transfer Learning with TAPE Roshan Rao Nicholas Bhattacharya Neil Thomas Yan Duan Xi Chen John F. Canny Pieter Abbeel Yun S. Song SSL 41 782 0 19 Jun 2019
A Decomposable Attention Model for Natural Language Inference Ankur P. Parikh Oscar Täckström Dipanjan Das Jakob Uszkoreit 213 1,367 0 06 Jun 2016