Jaume Bonet

ModCRElib is a package for modeling cis-regulatory elements, offering tools for TF-DNA interaction analysis, binding motif prediction, and regulatory complex modeling.

This paper introduces a framework for de novo protein design that automatically generates structural templates and evaluates their stability through experimental characterization.

The paper introduces a structure-based learning approach to predict TF binding preferences and model TF regulatory complexes, demonstrating its effectiveness over existing methods in cases of remote homology.

RosettaSurf is a computational design method that optimizes protein surfaces for functional sites, showing success in generating epitope mimics through surface-centric design.

RADI improves the computational efficiency of direct-coupling analysis by reducing the alphabet size, achieving faster execution with comparable or better accuracy than traditional methods.

The paper develops a computational method to predict DNA-binding preferences of C2H2-ZF domains using structural models and applies it to predict CTCF's binding sites.

The paper identifies mutations in the influenza A virus nucleoprotein that enable escape from importin-7 mediated nuclear import but reduce replicative fitness in human cells.

This paper introduces a computational framework for designing functional proteins by integrating folding and sequence design, showing that functional motifs can be embedded without requiring the global energy minimum.

rstoolbox provides tools for analyzing protein design ensembles, enabling efficient processing of decoy sets and benchmarking of design protocols.