Comparative Genomics

Group leader:  Toni Gabaldón

The main research interest of our group is to understand the complex relationships between genome sequences and phenotypes and how these two features evolve across species. We generally use large-scale phylogenetics approaches that allow looking at the evolution of genomes from the perspective of all of their genes, and we apply these analyses to a variety of biological questions related the evolution and function of organelles, pathways, and protein families. We have a special interest in understanding processes related to human pathogenesis (emergence of infectious disease, and organelle-related genetic diseases).

Through collaborations with experimental groups we apply comparative genomics to discover new mechanisms and genes involved in interesting processes, especially those of clinical relevance (see lines of research). Given that we work in an emerging field and we are exposed to new types and scales of data, we often have the need to develop novel bioinformatics tools to fill in existing gaps.

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PhylomeDB V4 released

The new version of PhylomeDB has been released. Version 4  

Open positions in Gabaldon's lab

We have several open positions in our lab, associated to several of our main lines of research. Please check the details here.

MetaPhOrs: orthologs and paralogs accross 829 genomes, based on multiple phylogenetic evidence

We have launched MetaPhOrs, a meta-method to predict orthology and paralogy from multiple phylogenetic evidence. To maximize reliability and coverage, we retrieved gene trees from PhylomeDB, Ensembl, TreeFam and Orthogroups. In addition we built maximum likelihood trees for orthologous gene families in OrthoMCL, COG, and EggNOG.


PhylomeDB v3.0 released

A new version of PhylomeDB has been released. With over 400.000 phylogenetic trees, PhylomeDB is currently the major public phylogenetic repository. It contains phylomes from model (Human, Yeast, Drosophila, Arabidopsis), but also alternative models such as the fungal pathogen Candida albicans, or the insects T. castaneum, N. vitripenis  and A. pisum.  New features have been added to the user's front end, including fully interactive tree images and link outs to external information.


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Analysis and manipulation of phylogenomic data using ETE

Organized by the Gabaldon's lab at CRG and The Gulbenkian Training Programme in Bioinformatics (GTPB)

 Location: Oerias, Portugal

Dates:from 23rd June to 25th June, 2010

More Information and application


Wed, 2010-06-23 09:00 - Fri, 2010-06-25 19:53


DeathBase: a database on structure, evolution and function of proteins involved in apoptosis and other forms of cell death.

Deathbase, a database of proteins involved in cell death has been officialy launched. This database compiles relevant data on the function, structure and evolution of proteins involved in apoptosis and other forms of cell death in several organisms. DeathBase  is a joint effort betwen Gabaldon's group at CRG and the lab of Muñoz-Pinedo at IDIBELL. 


The pea aphid genome fully-sequenced.

Two of the groups in our programme (Gabaldón and Guigó) have participated in the analysis of the genomic sequence of the pea aphid Acyrtosiphon pisum, published this week in PLoS Biology. This first published genome of a basal hemimetabolous insect, provides an out-group for comparison with other sequenced insects, and pavesthe way to elucidate molecular mechanisms in


ETE: A python Environment for Tree Exploration, published

ETE our python Environment for Tree Exploration has just been published:

Jaime Huerta-Cepas, Joaquín Dopazo and Toni Gabaldón. ETE: a python Environment for Tree Exploration. BMC Bioinformatics 2010, 11:24. [ link ]


trimAl 1.2 has been released

Multiple sequence alignments (MSA) are central to many areas of bioinformatics and evolutionary biology. They are not only used in the phylogenetic analyses of biological sequences but also in many other bioinformatics applications such as homology modeling, database searchers and motif finding. Recently, such multiple sequence alignment based techniques have been incorporated in high-throughput pipelines such as genome annotation and large-scale phylogenetics.


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