PREGO: A Literature and Data-Mining Resource to Associate Microorganisms, Biological Processes, and Environment Types.

To elucidate ecosystem functioning, it is fundamental to recognize what processes occur in which environments (where) and which microorganisms carry them out (who). Here, we present PREGO, a one-stop-shop knowledge base providing such associations. PREGO combines text mining and data integration techniques to mine such what-where-who associations from data and metadata scattered in the scientific literature and in public omics repositories. Microorganisms, biological processes, and environment types are identified and mapped to ontology terms from established community resources. Analyses of comentions in text and co-occurrences in metagenomics data/metadata are performed to extract associations and a level of confidence is assigned to each of them thanks to a scoring scheme. The PREGO knowledge base contains associations for 364,508 microbial taxa, 1090 environmental types, 15,091 biological processes, and 7971 molecular functions with a total of almost 58 million associations. These associations are available through a web portal, an Application Programming Interface (API), and bulk download. By exploring environments and/or processes associated with each other or with microbes, PREGO aims to assist researchers in design and interpretation of experiments and their results. To demonstrate PREGOs capabilities, a thorough presentation of its web interface is given along with a meta-analysis of experimental results from a lagoon-sediment study of sulfur-cycle related microbes

PREGO: A Literature and Data-Mining Resource to Associate Microorganisms, Biological Processes, and Environment Types

To elucidate ecosystem functioning, it is fundamental to recognize what processes occur in which environments (where) and which microorganisms carry them out (who). Here, we present PREGO, a one-stop-shop knowledge base providing such associations. PREGO combines text mining and data integration techniques to mine such what-where-who associations from data and metadata scattered in the scientific literature and in public omics repositories. Microorganisms, biological processes, and environment types are identified and mapped to ontology terms from established community resources. Analyses of comentions in text and co-occurrences in metagenomics data/metadata are performed to extract associations and a level of confidence is assigned to each of them thanks to a scoring scheme. The PREGO knowledge base contains associations for 364,508 microbial taxa, 1090 environmental types, 15,091 biological processes, and 7971 molecular functions with a total of almost 58 million associations. These associations are available through a web portal, an Application Programming Interface (API), and bulk download. By exploring environments and/or processes associated with each other or with microbes, PREGO aims to assist researchers in design and interpretation of experiments and their results. To demonstrate PREGO’s capabilities, a thorough presentation of its web interface is given along with a meta-analysis of experimental results from a lagoon-sediment study of sulfur-cycle related microbes

0s and 1s in marine molecular research: a regional HPC perspective

International audienceAbstract High-performance computing (HPC) systems have become indispensable for modern marine research, providing support to an increasing number and diversity of users. Pairing with the impetus offered by high-throughput methods to key areas such as non-model organism studies, their operation continuously evolves to meet the corresponding computational challenges. Here, we present a Tier 2 (regional) HPC facility, operating for over a decade at the Institute of Marine Biology, Biotechnology, and Aquaculture of the Hellenic Centre for Marine Research in Greece. Strategic choices made in design and upgrades aimed to strike a balance between depth (the need for a few high-memory nodes) and breadth (a number of slimmer nodes), as dictated by the idiosyncrasy of the supported research. Qualitative computational requirement analysis of the latter revealed the diversity of marine fields, methods, and approaches adopted to translate data into knowledge. In addition, hardware and software architectures, usage statistics, policy, and user management aspects of the facility are presented. Drawing upon the last decade’s experience from the different levels of operation of the Institute of Marine Biology, Biotechnology, and Aquaculture HPC facility, a number of lessons are presented; these have contributed to the facility’s future directions in light of emerging distribution technologies (e.g., containers) and Research Infrastructure evolution. In combination with detailed knowledge of the facility usage and its upcoming upgrade, future collaborations in marine research and beyond are envisioned

EOSC-Life Report on the work of the Open Call Projects

This Deliverable 3.3 is a report on the Digital Life Sciences Open Call and two Internal Calls organised by EOSC-Life WP3. The organisation of these Calls followed the successful integration and support of 8 Demonstrator projects&nbsp;which provided the first concrete use cases in the initial phase of EOSC-Life. The three Calls overall supported 11 scientific user projects, selected to facilitate integration of concrete use-cases across Life Sciences domains into the European Open Science Cloud (EOSC)&nbsp;framework. Through the Calls, the practical goal was to facilitate co-creation of an open, digital collaborative space for life science research by developing FAIR&nbsp;tools, workflows, resources, infrastructures, and guidelines together with the EOSC-Life RIs experts and communities. We report in this Deliverable the following achievements: Organisation of the EOSC-Life Open and Internal Calls; Integrating and training the EOSC-Life WP3 Open Call&nbsp;and Internal Call&nbsp;project teams in EOSC-Life; Activities for connecting project teams with EOSC-Life and LS-RI communities and dissemination of projects outcomes to broader communities; Work done in the individual projects, their results, and impact of developed resources; Recommendations from the EOSC-Life WP3 project teams and the EOSC-Life community for future Open Calls. </ol