COMPUTATIONAL SYSTEMS BIOLOGY GROUP

Welcome to the web space of the Computational Systems Biology Group. We are integrated in the Systems Biology Program of the National Centre for Biotechnology (CNB-CSIC). Our group is interested in different aspects of Bioinformatics, Computational Biology and Systems Biology. Our goal is to obtain new biological knowledge with an "in-silico" approach which complements the "in-vivo" and "in-vitro" methodologies of Biology. This mainly involves mining the massive amounts of information stored in biological databases.

Model of the p37 protein from T4 phage

ODCs - Connections between rare diseases through shared genes and protein interactions

Prediction of functional residues in proteins

The biodegradation network

The biodegradation network

Biological significance of GeneOntology biological processes

Biological significance of GeneOntology biological processes

Model of a TF-based construct

MBROLE server

Functional interpretation of metabolomics data

Breaking-Cas server @BioinfoGP

Sequence determinants of ATP hydrolysis asymmetry in the CCT chaperonins

Evolution of the ecosystem of software tools supporting research in molecular biology

Rational design of a Jasmonate antagonist

Functional annotation at the domain level

Functional annotation at the domain level

Relationships between biological entities extracted from the literature

Model of A. thaliana COI

Practical Protein Bioinformatics book

Model of the gp17 protein from T7 phage

Extraction of metabolite co-dependencies from metabonomics data

Prediction of chemical compound biodegradability

Phylogeny-independent prediction of functional residues

Co-evolutionary analysis of protein multiple sequence alignments

Determinants of the amino-acid racemases substrate specificity

Relationship between protein functional features and mRNA local translation speed

Model of the gp17 protein from T7 phage

Global analysis of protein disorder in A. thaliana

Mirrortree - Co-evolution-based prediction of protein interactions

JDet software

Mirrotree server

Prediction of protein interaction partners using physical docking

Detection of significant protein co-evolution

Detection of genomic regions with informative epigenetic patterns

Profile-based approach for predicting chemical compound pathways

Last updates
& changes

MBROLE 3.0 - Updated server for the functional analysis of metabolomics datasets. Lopez-Ibañez et al, 2023

CoMent server for browsing millions of relationships between biomedical concepts inferred from the scientific literature. Pazos et al, 2022

We have moved all web pages and services to a new web server. If you detect any problem, please let us know.

iFragMent server - Profile-based approach for predicting biological pathways of chemical compounds [Pubmed:34118870]