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This site provides access to the research output of the institution. Users may set up Atom or RSS feeds to be alerted to new content. The interface is available in English.

The Database of Genomic Variants archive (DGVa) is a repository that provides archiving, accessioning and distribution of publicly available genomic structural variants, in all species.

The IPD-NHKIR database provides a centralised repository for non-human KIR (NHKIR) sequences. Killer-cell Immunoglobulin-like Receptors (KIR) have been shown to be highly polymorphic at the allelic and haplotypic level. KIRs are members of the immunoglobulin superfamily (IgSF) formerly called Killer-cell Inhibitory Receptors. They are composed of two or three Ig-domains, a transmembrane region and cytoplasmic tail which can in turn be short (activatory) or long (inhibitory). The Leukocyte Receptor Complex (LRC) which encodes KIR genes has been shown to be polymorphic, polygenic and complex like the MHC.

PomBase is a model organism database that provides organization of and access to scientific data for the fission yeast Schizosaccharomyces pombe. PomBase supports genomic sequence and features, genome-wide datasets and manual literature curation as well as providing structural and functional annotation and access to large-scale data sets.

LIPID Metabolites And Pathways Strategy (LIPID MAPS®) is a multi-institutional supported website and database that provides access to a large number of globally used lipidomics resources. LIPID MAPS® has internationally led the field of lipid curation, classification, and nomenclature since 2003. We strive to produce new open-access databases, informatics tools and lipidomics-focused training activities will be generated and made publicly available for researchers studying lipids in health and disease. LIPID MAPS® is currently funded by a multi-institutional grant from Wellcome, held jointly by Cardiff University, University of California San Diego, the Babraham Institute Cambridge, and Swansea University, as well as an Innovation Study funded by ELIXIR. This current phase will see that LIPID MAPS® is maintained and importantly, further developed in line with the global demand and development of lipidomics. LIPID MAPS® has an internationally recognized classification system and the largest curated lipid structure database in the world.

Through the generous support of The Polonsky Foundation, this project made 1.5 million digitized pages freely available. Portions of the Biblioteca Apostolica Vaticana (Vatican Library) and the Bodleian Libraries’ collections of Hebrew manuscripts, Greek manuscripts, and incunabula were selected for digitization by a team of scholars and curators from around the world. The selection process was informed by a balance of scholarly and practical concerns; conservation staff at the Bodleian and Vatican Libraries worked with curators to assess not only the significance of the content, but the physical condition of the items, prioritizing items that are robust enough to withstand being transported to the imaging studio and handled by the photographers. In order to preserve the integrity and completeness of the manuscript collections, the libraries also agreed to digitize whole collections where appropriate. While the Vatican and the Bodleian had been creating digital images from our collections for a number of years, this project provided an opportunity for both libraries to increase the scale of their digitization services. In both cases, this meant significant investments in the equipment, infrastructure and people that make digitization possible. Over the course of this project, both libraries also revealed information about their digitization techniques and methods.

mirDNMR is a database for the collection of gene-centered background DNMRs obtained from different methods and population variation data. The database has the following functions: (i) browse and search the background DNMRs of each gene predicted by four different methods, including GC content (DNMR-GC), sequence context (DNMR-SC), multiple factors (DNMR-MF) and local DNA methylation level (DNMR-DM); (ii) search variant frequencies in publicly available databases, including ExAC, ESP6500, UK10K, 1000G and dbSNP and (iii) investigate the DNM burden to prioritize candidate genes based on the four background DNMRs using three statistical methods (TADA, Binomial and Poisson test). In conclusion, mirDNMR can be widely used to identify the genetic basis of sporadic genetic diseases.