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The Biodiversity Literature Repository (BLR) is a research infrastructure (RI) comprising the BLR Community on Zenodo at the European Center for Nuclear Research (CERN), and services to search and retrieve the data (Ocellus, Zenodeo API, BLR website). BLR’s focus is on biodiversity data liberated from scholarly publications, and it uses custom metadata linking to external vocabularies covering the needs of the biodiversity community. This includes taxonomic treatment or figures as well as the deposit of the original article annotated with metadata describing the data contained in the articles itself, as well as related identifiers for figures and and treatments therein. The main data import is through TreatmentBank or via publishers such as Pensoft. With over 650,000 deposits, BLR is the single largest community in Zenodo. Its data is widely reused, for example by the Global Biodiversity Information Facility (GBIF). All data in BLR is published under the CC0 Public Domain Dedication, remaining free for anyone to use, anywhere, for any purpose.

This site provides access to the research output of the institution. The interface is available in Spanish.

This site is an institutional repository which provides open access to the publications produced by the members of the University. The interface is in Spanish.

MetaNetX/MNXref is a database for reconciliation of metabolites and biochemical reactions to bring together genome-scale metabolic networks. The tools developed at MetaNetX are useful for accessing, analysing and manipulating metabolic networks. MetaNetX goal is to automate model construction and genome annotation for large-scale metabolic networks.

DisGeNET is a discovery platform containing one of the largest collections available of genes and variants involved in human diseases. DisGeNET integrates data from expert curated repositories, GWAS catalogues, animal models, and the scientific literature, and covers the whole landscape of human diseases. The current version of DisGeNET (v7.0) contains 1,134,942 gene-disease associations (GDAs), between 21,671 genes and 30,170 diseases, disorders, traits, and clinical or abnormal human phenotypes, and 369,554 variant-disease associations (VDAs), between 194,515 variants and 14,155 diseases, traits, and phenotypes. The data are homogeneously annotated with controlled vocabularies and community-driven ontologies. Additionally, several original metrics are provided to assist the prioritization of genotype-phenotype relationships. The information is accessible through a web interface, a Cytoscape App, an RDF SPARQL endpoint, a REST API, and an R package.

The Eukaryotic Promoter Database (EPD) provides accurate transcription start site (TSS) information for promoters of 15 model organisms, from human to yeast to the malaria parasite Plasmodium falciparum. While the original database was a manually curated database based on published experiments, new promoter collections are now produced entirely automatically (under the name “EPDnew”) based on high-throughput transcript mapping data and high-quality gene annotation resources. Corresponding functional genomics data can be viewed in a genome browser, queried or analyzed via web interfaces, or exported in standard formats like FASTA or BED for subsequent analysis with other tools; of note, EPD is tightly integrated with two tool suites developed by our group: ChIP-Seq and Signal Search Analysis, for analysis of chromatin context and sequence motif respectively. EPD provides promoter viewers, designed with the aim of integrating and displaying information from different sources about, for instance, histone marks, transcription factor-binding sites or SNPs with known phenotypes. These viewers rely upon the UCSC genome browser as a visualization platform, which enables users to view data tracks from EPD jointly with tracks from UCSC or public track hubs.

PMut Data Repository collects predictions of the pathological effect of all possible single amino acid variants on Uniref Human protein sequences. Predictions were prepared using PMut 2017 predictor (2017 version).