Bioinformatics and Genomics
1988 Ph.D. in Statistics. Universitat de Barcelona. (Spain).
1988-1993 Postdoctoral researcher at the Molecular Biology Computer Research Resource. Dana Farber Cancer Institute, Harvard University (Division of Biostatistics) BioMolecular Engineering Research Center. Boston University and Theoretical Biology And Biophysics Group (Los Alamos national Laboratory).
Since 1994 Investigator at Institut Municipal d’Investigació Mèdica (IMIM). Barcelona, (Spain).
Since 2001 Associate Professor at the Universitat Pompeu Fabra and coordinator of the Bioinformatics Programme at the Centre de Regulació Genòmica, Barcelona, (Spain).
Gene expression patterns may help determine time of death (13/02/2018)
International team of scientists led by CRG programme coordinator Roderic Guigó shows that changes in gene expression in different tissues can be used to predict the time of death of individuals.
National Research Award 2017 to Roderic Guigó (27/12/2017)
Roderic Guigó, coordinator of the CRG Bioinformatics and Genomics Programme, honored with the highest recognition for research excellence in Catalonia.
A new method accelerates the mapping of genes in the “Dark Matter” of our DNA (06/11/2017)
Scientists at the Centre for Genomic Regulation (CRG) in Barcelona, have developed a new method, which improved the most important catalogue of genes -GENCODE-, including characterization of new genes in the DNA “Dark Matter”.
Genome Editing: Pressing the «Delete» Button on DNA (02/03/2017)
Until recently, genomics was a «read-only» science. But scientists led by Rory Johnson at the University of Bern and the Centre for Genomic Regulation in Barcelona, have now developed a tool for quick and easy deletion of DNA in living cells. This software will boost efforts to understand the vast regions of non-coding DNA, or «Dark Matter», in our DNA and may lead to discovery of new disease-causing genes and potential new drugs.
Spanish scientists sequence the genome of the Iberian lynx, the most endangered felid (14/12/2016)
Genomic analysis of the Iberian lynx confirms that it is one of the species with the least genetic diversity among individuals, which means that it has little margin for adaptation.
The Blueprint project celebrates major manuscript release (18/11/2016)
BLUEPRINT scientists, including researchers at the Centre for Genomic Regulation, release a collection of 25 publications in Cell, Cell Press-associated and other high-impact journals. These are part of a package of 41 publications by the International Human Epigenome Consortium (IHEC) of which BLUEPRINT is a member.
'Blueprint' study of epigenetics of blood cells will serve biology and medicine (07/09/2016)
Researchers from the EU-funded BLUEPRINT project join their international colleagues this week at the 2016 International Human Epigenome Consortium (IHEC) conference in Brussels to report the latest results in understanding blood cell development and blood disease.
CRG researchers contribute to the sequencing of the Turbot genome (09/03/2016)
The first vertebrate to be genetically sequenced in Spain, the Turbot (Scophthalmus maximus), has a much more refined visual system than other fish as it has evolved to adapt to the shortage of light of the seabed. In addition, the fat in its cell membranes are far higher than in other species to withstand the low water temperatures in its habitat.
The mesoamerican bean genome decoded (25/02/2016)
An Ibero-American team of scientists decoded the Mesoamerican variety of the bean genome coinciding with the celebration of the International Year of Pulses, as designated by the United Nations.
Datasets and resources
This site provides a series of programs for the functional investigation of groups of genes, based on the Gene Ontology resource.
GRAPE 2.0 provides an extensive pipeline for RNA-Seq analyses.
GRAPE 2.0 provides an extensive pipeline for RNA-Seq analyses. It allows the creation of an automated and integrated workflow to manage, analyse and visualize RNA-Seq data.
The integrative pipeline for splicing analyses
The integrative pipeline for splicing analyses (IPSA); 1) Quantifies splice junctions and splice boundaries; 2) Calculates splicing indices, exon- and intron-centric; 3) analyzes micro-exons and local splice-graph structure
meta is a program to produce and to align the TF-maps of two gene promoter regions.
meta is a program is a program developed at Fundació Institut Mar d’Investigacions Mèdiques (IMIM) in collaboration with CRG (Roderic Guigó group) to produce and to align the TF-maps of two gene promoter regions. meta is very useful to characterize promoter regions from orthologous genes, or from co-regulated genes in microarrays, as it reduces the signal/noise ratio in a very significant manner, still detecting the real functional sites.
For more information about this software, please click here
mmeta is a program to produce and to align the TF-maps of multiple promoter regions.
mmeta is a program to produce and to align the TF-maps of multiple promoter regions. mmeta is very powerful to characterize promoter regions from multiple orthologous genes, or from co-regulated genes in microarrays, as it reduces the signal/noise ratio in a very significant manner, still detecting the real functional sites.
overlap is a program that computes the overlap between two sets of genomic features.
overlap is a program that computes the overlap between two sets of genomic features. More precisely it takes two gff files of genomic features as input and for each feature of the first set, says whether it is overlapped by a feature of the second set (basic mode, however more and more precise information can be retrieved).
PATRONUS is a program designed to compute in a very fast way the exact probability of observing a given number of occurrences of a simple motif in a sequence.
PATRONUS (from "PATtern Recognition by Optimized Numerical Universal Scoring") is a program designed to compute in a very fast way the exact probability of observing a given number of occurrences of a simple motif (that is, a continuous word without gaps) in a sequence. Its intended scope is the analysis of very long biological sequences, like chromosomes or whole genomes of complex organisms. The probability is computed on the basis of the Markovian statistics of order m for the sequence, that is the recorded number of the occurrences of all the submotifs of length m + 1 in the sequence. Contrary to what many people believe, computing such a probability for a generic motif is a computationally demanding task, mainly because motifs can overlap in non-trivial ways.