Diversity and conservation of the cave fauna of Crete (Greece)

Located in the southernmost of the Aegean Sea, Crete is the largest of the Greek islands covering an area of 8,261 km2. The first records on the cave fauna of Crete were published in 1869 and since then a total of 175 publications have been gradually increased our knowledge on the cave-dwelling species of the island. Crete is currently the best-studied Region of Greece regarding biospeleology. Although it covers only 6.3% of the national area, the faunistically investigated caves represent 35% of the investigated caves of Greece while the recorded cave fauna includes 30% of the cavernicolous species of Greece. In total, 250 species belonging to 166 genera, 83 families, 36 orders, 13 classes, and 5 phyla, have been recorded from 158 caves.  The most diverse groups are Araneae (64 species), Isopoda (29 species), Gastropoda, Copepoda, and Coleoptera (21 species each), Pseudoscorpiones (17 species) and Chiroptera (15 species). Among the invertebrate species, 102 are endemic to Greece of which 92 are Cretan endemics. The obligate cavernicolous fauna includes 42 species, most of them in Isopoda (13), Araneae (11) and Pseudoscorpiones (11). Only 3 species are distributed outside Greece, the isopods Libanonethes probosciferus Vandel, 1955 and Trichonethes kosswigi Strouhal, 1953. The cave habitats and the cave fauna of Greece are quite neglected in Greece’s environmental legislation and policy. Furthermore, there is an implementation gap in the environmental law. In Crete, 62 out of the previously mentioned 158 caves happened to be situated within protected areas (wildlife refuges and/or Natura 2000 sites). With the exception of the bat species, no other cave associated species is protected by specific law. Further efforts are also needed to assess the conservation status of most of the species. Out of 250 species only 35 have been assessed for IUCN Red List and 51 for Greece’s Red Data Book. Most of them are bats, gastropods and isopods

A comprehensive database for the cave fauna of Greece

Within the framework of the project “Conservation of the Cave Fauna of Greece”, the Hellenic Institute of Speleological Research developed the Cave Fauna of Greece (CFG) Database (https://database.inspee.gr/, Fig. 1), a free online data infrastructure that provides reliable information on the taxonomy, distribution, conservation status and referenced literature for all cavernicolous animal species in Greece. Furthermore, it provides information on geography, protection status and the fauna of each cave, as well as the referenced literature. The database was compiled after gathering, critically evaluating and integrating all taxonomic and faunistic information for species recorded in the caves of Greece. It includes all species recorded up to date and currently regarded as valid. The taxonomic reference system is harmonized with the Pan-European Species directories Infrastructure (PESI, EU-nomen). Considerable effort was also made to find the locations of the caves and to solve problems of synonymies, misspellings, etc. CFG database is a comprehensive, dynamic and digitally-available reference for several user-groups: research scientists, policy and decision-makers, nature conservation community, the education community, and citizen scientists. It was developed and launched to serve as a basic tool for research and conservation policies of cave species and caves in Greece. Currently, it hosts 2,567 records of 843 valid species in 465 caves, 763 literature references for species and more than 440 cave descriptions references. The user can navigate through 3 themes: fauna, caves, and references. A species can be found either by searching the name (or part of it) or by browsing through the taxonomic hierarchy to look for names of organisms within a group. A cave can be found either by searching the name/synonym (or part of it) or by browsing through the administrative hierarchy. Navigation from species to caves and vice versa can be performed through the names of species and caves

A comprehensive database for the cave fauna of Greece

Within the framework of the project “Conservation of the Cave Fauna of Greece”, the Hellenic Institute of Speleological Research developed the Cave Fauna of Greece (CFG) Database (https://database.inspee.gr/, Fig. 1), a free online data infrastructure that provides reliable information on the taxonomy, distribution, conservation status and referenced literature for all cavernicolous animal species in Greece. Furthermore, it provides information on geography, protection status and the fauna of each cave, as well as the referenced literature. The database was compiled after gathering, critically evaluating and integrating all taxonomic and faunistic information for species recorded in the caves of Greece. It includes all species recorded up to date and currently regarded as valid. The taxonomic reference system is harmonized with the Pan-European Species directories Infrastructure (PESI, EU-nomen). Considerable effort was also made to find the locations of the caves and to solve problems of synonymies, misspellings, etc. CFG database is a comprehensive, dynamic and digitally-available reference for several user-groups: research scientists, policy and decision-makers, nature conservation community, the education community, and citizen scientists. It was developed and launched to serve as a basic tool for research and conservation policies of cave species and caves in Greece. Currently, it hosts 2,567 records of 843 valid species in 465 caves, 763 literature references for species and more than 440 cave descriptions references. The user can navigate through 3 themes: fauna, caves, and references. A species can be found either by searching the name (or part of it) or by browsing through the taxonomic hierarchy to look for names of organisms within a group. A cave can be found either by searching the name/synonym (or part of it) or by browsing through the administrative hierarchy. Navigation from species to caves and vice versa can be performed through the names of species and caves

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

Arena3Dweb: interactive 3D visualization of multilayered networks supporting multiple directional information channels, clustering analysis and application integration.

Arena3Dweb is an interactive web tool that visualizes multi-layered networks in 3D space. In this update, Arena3Dweb supports directed networks as well as up to nine different types of connections between pairs of nodes with the use of Bézier curves. It comes with different color schemes (light/gray/dark mode), custom channel coloring, four node clustering algorithms which one can run on-the-fly, visualization in VR mode and predefined layer layouts (zig-zag, star and cube). This update also includes enhanced navigation controls (mouse orbit controls, layer dragging and layer/node selection), while its newly developed API allows integration with external applications as well as saving and loading of sessions in JSON format. Finally, a dedicated Cytoscape app has been developed, through which users can automatically send their 2D networks from Cytoscape to Arena3Dweb for 3D multi-layer visualization. Arena3Dweb is accessible at http://arena3d.pavlopouloslab.info or http://arena3d.org

OnTheFly2.0: a text-mining web application for automated biomedical entity recognition, document annotation, network and functional enrichment analysis.

Extracting and processing information from documents is of great importance as lots of experimental results and findings are stored in local files. Therefore, extracting and analyzing biomedical terms from such files in an automated way is absolutely necessary. In this article, we present OnTheFly2.0, a web application for extracting biomedical entities from individual files such as plain texts, office documents, PDF files or images. OnTheFly2.0 can generate informative summaries in popup windows containing knowledge related to the identified terms along with links to various databases. It uses the EXTRACT tagging service to perform named entity recognition (NER) for genes/proteins, chemical compounds, organisms, tissues, environments, diseases, phenotypes and gene ontology terms. Multiple files can be analyzed, whereas identified terms such as proteins or genes can be explored through functional enrichment analysis or be associated with diseases and PubMed entries. Finally, protein-protein and protein-chemical networks can be generated with the use of STRING and STITCH services. To demonstrate its capacity for knowledge discovery, we interrogated published meta-analyses of clinical biomarkers of severe COVID-19 and uncovered inflammatory and senescence pathways that impact disease pathogenesis. OnTheFly2.0 currently supports 197 species and is available at http://bib.fleming.gr:3838/OnTheFly/ and http://onthefly.pavlopouloslab.info

OnTheFly2.0:a text-mining web application for automated biomedical entity recognition, document annotation, network and functional enrichment analysis

Extracting and processing information from documents is of great importance as lots of experimental results and findings are stored in local files. Therefore, extracting and analyzing biomedical terms from such files in an automated way is absolutely necessary. In this article, we present OnTheFly2.0, a web application for extracting biomedical entities from individual files such as plain texts, office documents, PDF files or images. OnTheFly2.0 can generate informative summaries in popup windows containing knowledge related to the identified terms along with links to various databases. It uses the EXTRACT tagging service to perform named entity recognition (NER) for genes/proteins, chemical compounds, organisms, tissues, environments, diseases, phenotypes and gene ontology terms. Multiple files can be analyzed, whereas identified terms such as proteins or genes can be explored through functional enrichment analysis or be associated with diseases and PubMed entries. Finally, protein-protein and protein-chemical networks can be generated with the use of STRING and STITCH services. To demonstrate its capacity for knowledge discovery, we interrogated published meta-analyses of clinical biomarkers of severe COVID-19 and uncovered inflammatory and senescence pathways that impact disease pathogenesis. OnTheFly2.0 currently supports 197 species and is available at http://bib.fleming.gr:3838/OnTheFly/ and http://onthefly.pavlopouloslab.info

OnTheFly(2.0): a text-mining web application for automated biomedical entity recognition, document annotation, network and functional enrichment analysis

Extracting and processing information from documents is of great importance as lots of experimental results and findings are stored in local files. Therefore, extracting and analyzing biomedical terms from such files in an automated way is absolutely necessary. In this article, we present OnTheFly(2.0), a web application for extracting biomedical entities from individual files such as plain texts, office documents, PDF files or images. OnTheFly(2.0) can generate informative summaries in popup windows containing knowledge related to the identified terms along with links to various databases. It uses the EXTRACT tagging service to perform named entity recognition (NER) for genes/proteins, chemical compounds, organisms, tissues, environments, diseases, phenotypes and gene ontology terms. Multiple files can be analyzed, whereas identified terms such as proteins or genes can be explored through functional enrichment analysis or be associated with diseases and PubMed entries. Finally, protein-protein and protein-chemical networks can be generated with the use of STRING and STITCH services. To demonstrate its capacity for knowledge discovery, we interrogated published meta-analyses of clinical biomarkers of severe COVID-19 and uncovered inflammatory and senescence pathways that impact disease pathogenesis. OnTheFly(2.0) currently supports 197 species and is available at http://bib.fleming.gr:3838/OnTheFly/and http://onthefly.pavlopouloslab.info

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