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Clinical and Translational Bioinformatics

Our main research aims at understanding the molecular basis of hereditary disease, integrating two complementary aspects: the molecular impact of genetic variants and the regulatory role of genetic background. At a technical level, to reach our objective, we integrate the results of the most advanced genomic experiments (single-cell RNAsq, NGS sequencing, etc.) using state-of-the-art machine learning tools.

As a result of our efforts, we have recently made significant advances in understanding the functional effect of BRCA1/2 protein variants underlying hereditary breast and ovarian cancers. In fact, the methodology developed earned us the second position in the group classification at the international competition CAGI 5, held in 2019.

Team

Fco. Xavier De la Cruz Montserrat

Fco. Xavier De la Cruz Montserrat

Head of group
Clinical and Translational Bioinformatics
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Aitana Diaz Vazquez

Aitana Diaz Vazquez

Research technician
Clinical and Translational Bioinformatics
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Guerrero Flores, Javier

Guerrero Flores, Javier

Predoctoral researcher
Clinical and Translational Bioinformatics
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Selen Ozkan

Selen Ozkan

Postdoctoral researcher
Clinical and Translational Bioinformatics
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Shaopei Ye

Shaopei Ye

Predoctoral researcher
Clinical and Translational Bioinformatics
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Fco. Xavier De la Cruz Montserrat

Fco. Xavier De la Cruz Montserrat

Head of group
Clinical and Translational Bioinformatics
Read more
Aitana Diaz Vazquez

Aitana Diaz Vazquez

Research technician
Clinical and Translational Bioinformatics
Read more
Guerrero Flores, Javier

Guerrero Flores, Javier

Predoctoral researcher
Clinical and Translational Bioinformatics
Read more
Selen Ozkan

Selen Ozkan

Postdoctoral researcher
Clinical and Translational Bioinformatics
Read more
Shaopei Ye

Shaopei Ye

Predoctoral researcher
Clinical and Translational Bioinformatics
Read more

Research lines

Biomarker development

IP: -

Prediction of pathological mutations

Since a few years ago, we have been working in the development of computational tools for the prediction of pathological mutations in proteins (PMID: 11812146, 15390262, 15879453, 16208716, 17059831). In this work we have followed a two-step approach. First, we have characterized pathological mutations in terms of sequence, structure and evolutionary properties (PMID: 11812146). Second, we have used the results of this descriptive work to identify those parameters with the best predictive power. Also we have used these results to train a neural network and obtain an empirical model that allows the identification of disease-causing mutations with moderately high accuracies (around 70%; PMID: 15390262, 15879453, 16208716).

At present, we are applying this approach to the case of specific diseases. We believe that this is a natural step towards the advancement of personalized medicine. Within this context, we are characterizing the impact on the structure and function of alpha-galactosidase of Fabry disease-causing mutations. Again our approach is the same as in the general case, but here we are benefitting from the close collaboration with the group of Dr. Joan Montaner. 

IP: Fco. Xavier De la Cruz Montserrat

Projects

Avanzando hacia el diagnóstico de precisión a través de la comprensión mecanística de las patologias: de la interpretación de variantes a la identificación del perfil celular.

IP: Fco. Xavier De la Cruz Montserrat
Collaborators: Miriam Izquierdo Sans, Javier Guerrero Flores
Funding agency: Ministerio de Ciencia e Innovación-MICINN
Funding: 111758
Reference: PREP2022-000566
Duration: 01/02/2024 - 31/01/2028

Ministerio de Ciencia

Advancing towards precision diagnostics using a mechanistic understanding of disease processes: from variant interpretation to single-cell profiling

IP: Fco. Xavier De la Cruz Montserrat
Collaborators: Advancing towards precision diagnostics using a mechanistic understanding of disease processes: from variant interpretation to s, Advancing towards precision diagnostics using a mechanistic understanding of disease processes: from variant interpretation to s
Funding agency: Ministerio de Ciencia e Innovación-MICINN
Funding: 262500
Reference: PID2022-142753OB-I00
Duration: 01/09/2023 - 31/08/2026

Ministerio de Ciencia

Thesis

Desarrollo de herramientas para el análisis y predicción patogénica de las variantes missense de ATM en el entorno clínico.

PhD student: Luz Marina Porras Monroy
Director/s: Fco. Xavier De la Cruz Montserrat
University: Universitat de Barcelona
Year: 2023

Binary pathogenicity classification missense variants through development of quantitative protein-specific predictors

PhD student: Selen Ozkan , Selen Ozkan , Selen Ozkan
Director/s: Fco. Xavier De la Cruz Montserrat
University: Universitat de Barcelona
Year: 2023

Novel approaches for in silico identification of pathogenic variants in BRCA1 and BRCA2 hereditary breast and ovarian cancer predisposition genes

PhD student: Natalia Padilla Sirera, Natalia Padilla Sirera, Natalia Padilla Sirera
Director/s: Fco. Xavier De la Cruz Montserrat
University: Universidad Autònoma de Barcelona
Year: 2020

A MACHINE LEARNING MODEL FOR IMPROVING THE ANNOTATION OF PROTEIN SEQUENCE VARIANTS IN SEQUENCING PROJECTS

PhD student: Elena Álvarez de la C Crespo
Director/s: Fco. Xavier De la Cruz Montserrat
University: Universitat de Barcelona
Year: 2019

ESTUDIO DE LAS PROPIEDADES CONFORMACIONALES DE LAS PROTEÍNAS MEDIANTE EL USO DE MODELOS DE BAJA RESOLUCIÓN BASADOS EN LA DISCRETIZACIÓN DE LAS COORDENADAS INTERNAS

PhD student: Francisco Martín Bandera
Director/s: Fco. Xavier De la Cruz Montserrat
University: Universitat de Barcelona
Year: 2018

Caracterització bioinformàtica de la relació entre l'impacte molecular de les variants patogèniques i el fenotip clínic

PhD student: Oscar Marín Sala
Director/s: Fco. Xavier De la Cruz Montserrat
University: Universidad Autònoma de Barcelona
Year: 2017

Novel approaches in the identification of pathogenic variants in the clinical diagnosis

PhD student: Maria Casandra Riera Ribas
Director/s: Fco. Xavier De la Cruz Montserrat
University: Universidad Autònoma de Barcelona
Year: 2016

Blog

News

The Clinical and Translational Bioinformatics Group at VHIR has been responsible for the computational analysis of two international genetic studies led by the Children's Hospital of Philadelphia.

The Clinical and Translational Bioinformatics group is launching the project to use cutting-edge artificial intelligence in the identification of pathogenic variants.