Francisco Rodrigues Pinto

Professor of Biochemistry

Faculty of Sciences, University of Lisbon

BioISI

Biography

I am professor of Biochemistry at the Faculty of Sciences, University of Lisbon and a researcher at the RNA Systems Biology group (Gama & Pinto Lab) within the Gene Expression Regulation unit of the Biosystems and Integrated Sciences Institute (BioISI). My research interests focus on networks of biological molecules that regulate cellular processes. To understand the structure and function of these networks, in health and disease states, we use and develop mathematical and computational methods.

Interests

Systems Biology
Biological Networks
Mathematical modeling of biological systems
Biostatistics

Education

PhD in Biochemistry, 2005

ITQB/UNL
BSc in Biochemistry (5 year degree), 2001

FCUL

Selected Publications

Searching the overlap between network modules with specific betweeness (S2B) and its application to cross-disease analysis

ML Garcia-Vaquero, M Gama-Carvalho, J De Las Rivas, FR Pinto

Fine-tuning of fgf8a expression through alternative polyadenylation has a selective impact on Fgf-associated developmental processes

SF Fernandes, R Fior, F Pinto, M Gama-Carvalho, L Saúde

A Mathematical Model of the Phosphoinositide Pathway

DV Olivença, I Uliyakina, LL Fonseca, MD Amaral, EO Voit, FR Pinto

Preprint PDF Code DOI

Opi1p translocation to the nucleus is regulated by hydrogen peroxide in Saccharomyces cerevisiae

C Camelo, F Vilas-Boas, AP Cepeda, C Real, J Barros-Martins, F Pinto, H Soares, HS Marinho, L Cyrne

Linking amyotrophic lateral sclerosis and spinal muscular atrophy through RNA-transcriptome homeostasis: a genomics perspective

M Gama-Carvalho, ML Garcia-Vaquero, FR Pinto, F Besse, J Weis, A Voigt, JB Schulz, J De Las Rivas

Research

Biological Networks

Development of methods to analyze biological networks, their relation to cellular processes and disease.

Mathematical Modeling

Apply mathematical modeling to quantitavely understand biological systems.

Tools

Comparing Partitions

Tools to compare clustering or classification results.

Local correlation

Tool to compute correlation between distances in two different spaces around objects located in both spaces.

Model of Phosphoinositide Metabolism

ODE model of phosphoinositide metabolism in a membrane patch.

NetSetStat

R functions to statistically characterize sets of nodes within interaction networks.

Ranked Adjusted Rand

Tool to compute agreement between partitions taking relative cluster distances into account.

Specific Specific Betweenness - S2B

Tool to predict proteins (network nodes) simultaneously associated with two diseases (network modules).

Teaching

Quantitative methods in Systems Biology
Research Design in Biochemistry
Experimental Project II (Network Biology module)
Experimental Biochemistry IV (Functional enrichment module)
Experimental Biochemistry II (Statistics module)