2 citations · 2 across the 2 of their papers we have counts for
3 papers
q-bio.QM2023
Multi-level Protein Representation Learning for Blind Mutational Effect Prediction
Yang Tan, Bingxin Zhou, Yuanhong Jiang +2
Directed evolution plays an indispensable role in protein engineering that revises existing protein sequences to attain new or enhanced functions. Accurately predicting the effects…
q-bio.QM2023★ 2 cited
Accurate and Definite Mutational Effect Prediction with Lightweight Equivariant Graph Neural Networks
Bingxin Zhou, Outongyi Lv, Kai Yi +4
Directed evolution as a widely-used engineering strategy faces obstacles in finding desired mutants from the massive size of candidate modifications. While deep learning methods le…
q-bio.QM2023
TemPL: A Novel Deep Learning Model for Zero-Shot Prediction of Protein Stability and Activity Based on Temperature-Guided Language Modeling
Pan Tan, Mingchen Li, Liang Zhang +2
We introduce TemPL, a novel deep learning approach for zero-shot prediction of protein stability and activity, harnessing temperature-guided language modeling. By assembling an ext…