arXiv | An Interpretable Framework Applying Protein Words to Predict Protein-Small Molecule Complementary Pairing Rules
ABSTRACT: Despite the high accuracy of 'black box' deep learning models, drug discovery still relies on protein-ligand interaction principles and heuristics. To improve interp…
iscience | Predicting Protein-Nucleic Acid Interactions via Protein Language Models with Biophysical and Evolutionary Priors
ABSTRACT: Protein interactions with nucleic acids are fundamental to numerous biological processes. Here, we present PNABPred, a multi-modal framework that integrates biophysi…
Congratulations on the Acceptance of a Paper by Dr. Hedi Chen in Advanced Science
Recently, a research article authored by Dr. Hedi Chen, a PhD graduate from our research group, entitled “Automatically Defining Protein Words for Diverse Functional Predictio…
Advanced Science | Automatically Defining Protein Words for Diverse Functional Predictions Based on Attention Analysis of a Protein Language Model
ABSTRACT: Understanding the relationship between protein sequence and function remains a longstanding challenge in bioinformatics, and to date the lion's share of related tool…
