Wouter Boomsma

APOSM improves generative small-molecule design by using pairwise preference learning to enhance surrogate model reliability and active candidate selection.

This study shows that ubiquitylation of UBQLN2's UBL domain regulates its stability and localization, with implications for proteasomal degradation and ALS.

This paper proposes a probabilistic approach to multiple sequence alignment using spatial transformations and deep learning to account for alignment uncertainty.

This paper investigates cross-species vs species-specific prediction of protein melting temperatures and finds that cross-species models perform no better than species-specific ones.

Kermut is a Gaussian process regression model for protein variant effect prediction that provides uncertainty estimates through its posterior.

This paper introduces SSEmb, a model that integrates protein sequence and structure to improve variant effect predictions and downstream tasks like binding site prediction.

This paper introduces DeepSPT, a deep learning framework that automates the analysis of sub-cellular diffusion to infer functional information, achieving high accuracy in identifying endosomal structures during viral infections.

The paper curates a benchmark dataset for exploring protein fitness landscapes using wildtype sequences and evaluates different representation paradigms for their predictive power.

This paper evaluates how different performance metrics and generalization definitions affect the assessment of protein regression models.

MembraneFold integrates protein structure and topology prediction to visualize transmembrane proteins, offering a web server for fast and accurate analysis.

Barnaba is a Python library for analyzing nucleic acids structures and molecular trajectories, offering tools for distance calculation, cluster analysis, motif search, and elastic network modeling.