PhD Thesis - Computational Science

Pérez A. Learning How to Simulate: applying machine learning methods to improve molecular dynamics simulations. Universitat Pompeu Fabra. January, 27th 2022. Thesis Director: De Fabritiis G.

2022

PhD Thesis - Computational Science

Herrera P. A Study of intrinsically disordered proteins using molecular dynamics simulations.  Universitat Pompeu Fabra. July, 17th 2020. Thesis Director: De Fabritiis G.

2020

PhD Thesis - Computational Science

Jiménez Luna J. Machine learning in structural biology and chemoinformatics: driving drug discovery one epoch at a time. Universitat Pompeu Fabra. October 24th, 2019. Thesis Director: De Fabritiis G.

2019

PhD Thesis - Computational Science

Martínez G. Applications of molecular dynamics in drug discovery and technology transfer via a web-based platform. Universitat Pompeu Fabra. December, 20th 2017. Thesis Director: de Fabritiis G.

2017

PhD Thesis - Integrative Biomedical Informatics - Computational Science

Ferruz N. Understanding ligand-receptor recognition by means of high-throughput molecular dynamics. A perspective for drug discovery. Universitat Pompeu Fabra. March, 4th, 2016. Thesis Director: De Fabritiis G. and Sanz F.

2016

PhD Thesis - Computational Science

Stanley N. Understanding disordered and membrane protein recognition by molecular dynamics. Universitat Pompeu Fabra. April, 24th, 2015. Thesis Director: De Fabritiis G.

2015

PhD Thesis - Computational Science

Buch I. Investigation of protein-ligand interactions using high-throughput all-atom molecular dynamics simulations. Universitat Pompeu Fabra. Director: Gianni de Fabritiis. June, 29 2012

2012