Felipe Vilicich

Inferring Dynamic Information from Protein Structures by Gaussian Integrals and Deep Learning

This paper develops a deep learning framework to predict protein flexibility from static structural data, achieving moderate accuracy and identifying key structural features associated with flexibility.

Structure-based Predictions of Conformational B Cell Epitopes by Protein Language Model and Deep Learning

The paper introduces a protein language model-based method to predict conformational B-cell epitopes on antigen structures, outperforming existing methods on benchmark datasets.

Multi-omics identification of extracellular components of the fetal monkey and human neocortex.

The paper identifies extracellular components in the developing fetal neocortex of humans and non-human primates using multi-omics approaches.