Computational Systems Biology

Computational Systems Biology Group (CNB-CSIC)

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).

Use the links above to access the different sections.

Prediction of functional residues in proteins

Effect of predicted accessibility on mirrortree

Biological significance of GeneOntology biological processes

Functional interpretation of metabolomics data

Sequence determinants of ATP hydrolysis asymmetry in the CCT chaperonins

Rational design of a Jasmonate antagonist

Functional annotation at the domain level

SNP-based characterization of mouse strains

Vectorial representation of chemical compounds and metabolic reactions

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

Global analysis of protein disorder in A. thaliana

Mirrortree - Co-evolution-based prediction of protein interactions

Prediction of protein interaction partners using physical docking

Events

XXII meeting of the Spanish Bioinformatics Network
21-24 September (Sevilla, Spain).
Sponsored by the Spanish National Bioinformatics Institute (INB)

22nd International Conference on Intelligent Systems for Molecular Biology ( ISMB'14 )
July 11-15, 2014 (Boston, USA)

Master en Bioinformática y Biología Computacional XII Edición
Septiembre 2014 - Junio 2015 (Instituto de Salud Carlos III, Madrid)

Last updates and changes

[NEW]
Three collaborations with experimental groups were recently published (PubMed: 24997606, 24420718 & 24419381)

A number of bugs have been corrected in JDet. You can find more information and the latest version with the bugs fixed at JDet's main page

Resources for the annotation and prediction of protein function at the domain level