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LW ERIC is the e-Science European Research Infrastructure for Biodiversity and Ecosystem Research. It provides access to a multitude of datasets, e-Services and tools enabling the construction and operation of Virtual Research Environments (VREs) through innovative technologies, which permit the accelerated capture of data, their analysis and knowledge-based decision-making support for biodiversity and ecosystem management. It can be split into 2 groups of services: BER_e-Infra & BER_VREs. BER_VREs consists of 3 cutting-edge technologies: LifeBlock, a Blockchain technology for transparency and immutability, guaranteeing FAIR-compliant data. Tesseract, the technical composability layer to integrate web services, enabling the development of VREs for users to combine and arrange services and software into multiple workflows. The Artificial Intelligence virtual laboratory (vLab), an online service allowing users to locate others working on similar subjects and the hubs that link them. Within BiCiKL, LW ERIC will support virtual access to BER_VREs.

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.

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

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.

The PR2 reference sequence database began as part of the BioMarks project from previous work in the Plankton Group of the Station Biologique of Roscoff. It aims to provide a reference database of carefully annotated 18S rRNA sequences using nine unique taxonomic fields (from domain to species). At present, it contains over 240,000 sequences. Although it focuses on protists, it also contains sequences from metazoa, fungi and plants as well a limited set of 16S sequences from plastids and bacteria. Several metadata fields are available for many sequences, including geo-localisation, whether it originates from a culture or a natural sample, and host type. The annotation of PR2 is performed by experts in each of the taxonomic groups.

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.

The Hydra repository was a digital archive for the University of Hull. It was developed to hold, manage, preserve and provide access to the growing body of digital material generated through the research, teaching and administrative activities of the University.