Systematic Evaluation of 566 Sequence-Based Features
for Predicting Protein Stability Changes Induced by
Mutations Using Machine Learning (Qiaobin Yao, Junyan
Li, Dongxiao Liu, Krish Wahi, Shaolei Teng)
Red Teaming Generative Proteins with Unsupervised
Toxin-Based Risk Embeddings (Tia Pope, Ahmad Patooghy)
Structural Impacts of Insertion Mutations on
Protein-Protein Interfaces (James Tessmer, Logan Day,
Bogdan Trigubov, Emilia Galant, Filip Jagodzinski)
PRIMRose: Insights into the Per-Residue Energy
Metrics of Proteins with Double InDel Mutations Using
Deep Learning (Stella Brown, Nicolas Preisig, Autumn
Davis, Brian Hutchinson, Filip Jagodzinski)
From Contrast to Control: Domain Conditioned Masking
for Small Molecule Generation of Quaternary Ammonium
Compounds (Shiva Ghaemi, Rehenuma Tasmin Rodosh, Shahana
Shultana, Amarda Shehu, Daniel Barbara)
Physics-Guided Active Learning for New Ligand
Discovery (Nikhil Dhiman, Dikshant Sagar, Negin
Forouzesh)
DyVarMap: An Interpretable, Dynamics-Aware Framework
for Missense Variant Classification (Yiyang Lian, Amarda
Shehu)
ConSOLAE: Learning Smooth and Generalizable
Representations for Protein Fold Recognition (Shraddha
Patre, Riya Kanani, Aarnav Tare, Pranavh Vallabhaneni,
Fardina Fathmiul Alam)
DeepSSETracer 2.0: Improved Deep Learning Model
Performance for Protein Secondary Structure Segmentation
from Cryo-EM Maps (Bryan Hawickhorst, Thu Nguyen, Willy
Wriggers, Jiangwen Sun, Jing He)
A Molecular Dynamics Study of Polyacrylamide
Conformational Changes in Ca2+ and Mg2+ Solutions
(Gideon K. Gogovi, Lorcan Cheng)
Benchmarking and Consensus Ranking of Inverse
Folding Models for Protein-Ligand Interface Design
(Yao Wei, Uliano Guerrini, Ivano Eberini
