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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Hannes Berg; Maria A. Wirtz Martin; Nadide Altincekic; Islam Alshamleh; +79 Authors

    Work at BMRZ is supported by the state of Hesse. Work in Covid19-NMR was supported by the Goethe Corona Funds, by the IWBEFRE-program 20007375 of state of Hesse, the DFG through CRC902: “Molecular Principles of RNA-based regulation.” and through infrastructure funds (project numbers: 277478796, 277479031, 392682309, 452632086, 70653611) and by European Union’s Horizon 2020 research and innovation program iNEXT-discovery under grant agreement No 871037. BY-COVID receives funding from the European Union’s Horizon Europe Research and Innovation Programme under grant agreement number 101046203. “INSPIRED” (MIS 5002550) project, implemented under the Action “Reinforcement of the Research and Innovation Infrastructure,” funded by the Operational Program “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014–2020) and co-financed by Greece and the EU (European Regional Development Fund) and the FP7 REGPOT CT-2011-285950—“SEE-DRUG” project (purchase of UPAT’s 700 MHz NMR equipment). The support of the CERM/CIRMMP center of Instruct-ERIC is gratefully acknowledged. This work has been funded in part by a grant of the Italian Ministry of University and Research (FISR2020IP_02112, ID-COVID) and by Fondazione CR Firenze. A.S. is supported by the Deutsche Forschungsgemeinschaft [SFB902/B16, SCHL2062/2-1] and the Johanna Quandt Young Academy at Goethe [2019/AS01]. M.H. and C.F. thank SFB902 and the Stiftung Polytechnische Gesellschaft for the Scholarship. L.L. work was supported by the French National Research Agency (ANR, NMR-SCoV2-ORF8), the Fondation de la Recherche Médicale (FRM, NMR-SCoV2-ORF8), FINOVI and the IR-RMN-THC Fr3050 CNRS. Work at UConn Health was supported by grants from the US National Institutes of Health (R01 GM135592 to B.H., P41 GM111135 and R01 GM123249 to J.C.H.) and the US National Science Foundation (DBI 2030601 to J.C.H.). Latvian Council of Science Grant No. VPP-COVID-2020/1-0014. National Science Foundation EAGER MCB-2031269. This work was supported by the grant Krebsliga KFS-4903-08-2019 and SNF-311030_192646 to J.O. P.G. (ITMP) The EOSC Future project is co-funded by the European Union Horizon Programme call INFRAEOSC-03-2020—Grant Agreement Number 101017536. Open Access funding enabled and organized by Projekt DEAL SARS-CoV-2 (SCoV2) and its variants of concern pose serious challenges to the public health. The variants increased challenges to vaccines, thus necessitating for development of new intervention strategies including anti-virals. Within the international Covid19-NMR consortium, we have identified binders targeting the RNA genome of SCoV2. We established protocols for the production and NMR characterization of more than 80 % of all SCoV2 proteins. Here, we performed an NMR screening using a fragment library for binding to 25 SCoV2 proteins and identified hits also against previously unexplored SCoV2 proteins. Computational mapping was used to predict binding sites and identify functional moieties (chemotypes) of the ligands occupying these pockets. Striking consensus was observed between NMR-detected binding sites of the main protease and the computational procedure. Our investigation provides novel structural and chemical space for structure-based drug design against the SCoV2 proteome. 12 pags., 4 figs., 3 tabs. Peer reviewed

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Angewandte Chemie In...arrow_drop_down
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    Angewandte Chemie International Edition
    Other literature type . Article . 2022
    License: CC BY
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    tuprints
    Article . 2024
    Data sources: tuprints
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    Fraunhofer-ePrints
    Other literature type . 2022
    Data sources: Fraunhofer-ePrints
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    Angewandte Chemie
    Article . 2022
    License: CC BY
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    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    https://doi.org/10.26083/tupri...
    Article . 2024
    License: CC BY
    Data sources: Datacite
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      image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ Angewandte Chemie In...arrow_drop_down
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      Angewandte Chemie International Edition
      Other literature type . Article . 2022
      License: CC BY
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      tuprints
      Article . 2024
      Data sources: tuprints
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      Fraunhofer-ePrints
      Other literature type . 2022
      Data sources: Fraunhofer-ePrints
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      Angewandte Chemie
      Article . 2022
      License: CC BY
      Data sources: Crossref
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      https://doi.org/10.26083/tupri...
      Article . 2024
      License: CC BY
      Data sources: Datacite
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Dritsou, Vicky; Ilvanidou, Maria; Despotidou, Isidora; Liakopoulou, Vicky; +2 Authors

    Humanities researchers often need to study heterogeneous digitized archives from different sources. But how can they deal with this heterogeneity, both in terms of structure and semantics? What are the digital tools they can use in order to integrate resources and study them as a whole? And what if they are unfamiliar with the methods and tools available? Towards this end, DARIAH-EU[1] and CLARIN[2] research infrastructures already support researchers in exploiting digital tools. Specific use case research scenarios have also been developed, with the PARTHENOS SSK[3] being a successful example. In this paper we describe our related (ongoing) experience from the development of the Greek research infrastructure APOLLONIS[4], where, among others, we have focused on identifying and supporting the workflows that researchers need to follow to perform specific research studies while jointly accessing disparate archives. Using the decade of 1940s as a use case, a turbulent period in Greek history due to its significant events (WWII, Occupation, Opposition, Liberation, Civil War), we have assembled (digitized) historical archives, coming from different providers and shedding light on different historical aspects of these events. From the acquisition of the resources to the desired outcome, we record the workflows of the whole research study, including the initial curation process of the digitized archives, the ingestion, the joint indexing of the data, the generation of semantic graph representations and, finally, their publication and searching. After the acquisition of the heterogeneous source materials we perform a detailed investigation of their structure and contents, in order to map the different archive metadata onto a common metadata schema, thus enabling joint indexing and establishing semantic relations among the contents of the archives. The next step is data cleaning, where messy records are cleaned and normalized. Natural Language Processing methods are then exploited for the extraction of additional information contained in the archival records or in free text metadata fields, such as persons, places, armed units, dates and topics, which enhance the initial datasets. The outcome is encoded in XML using the common schema and ingested into a repository through an aggregator implemented using the MoRE[5] system. A joint index based on a set of basic criteria is generated and maintained, thus ensuring joint access to all archival records regardless of their source. In addition, an RDF representation is generated from the encoded archival data, enabling their publication in the form of a semantic graph and supporting interesting complex queries. This is based on a specifically designed extension of CIDOC CRM[6] and a compilation of a list of research queries of varying complexity encoded in SPARQL. Preliminary tests of the entire workflows and the tools used in all steps yielded very encouraging results. Our immediate plans include full scale ingestion and indexing of the material from a number of archives, producing the corresponding semantic graph and streamlining the incorporation of new archives. [1]DARIAH-EU, https://www.dariah.eu/ [2]CLARIN, https://www.clarin.eu/ [3]PARTHENOS Standardization Survival Kit (SSK), http://www.parthenos-project.eu/portal/ssk-2 [4]APOLLONIS Greek Infrastructure for Digital Arts, Humanities and Language Research and Innovation, https://apollonis-infrastructure.gr/ [5]MoRE Aggregator, http://more.dcu.gr/ [6]CIDOC CRM, http://www.cidoc-crm.org/

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    ZENODO
    Other literature type . 2020
    License: CC BY
    Data sources: ZENODO
    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    ZENODO
    Presentation . 2020
    License: CC BY
    Data sources: Datacite
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      ZENODO
      Other literature type . 2020
      License: CC BY
      Data sources: ZENODO
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      Presentation . 2020
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  • image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
    Authors: Gazzarrini, Elena; Garcia, Enrique; Gosein, Domenic; Moya, Alba Vendrell; +2 Authors

    The Virtual Research Environment is an analysis platform developed at CERN serving the needs of scientific communities involved in European Projects. Its scope is to facilitate the development of end-to-end physics workflows, providing researchers with access to an infrastructure and to the digital content necessary to produce and preserve a scientific result in compliance with FAIR principles. The platform's development is aimed at demonstrating how sciences spanning from High Energy Physics to Astrophysics could benefit from the usage of common technologies, initially born to satisfy CERN's exabyte-scale data management needs. The Virtual Research Environment's main components are (1) a federated distributed storage solution (the Data Lake), providing functionalities for data injection and replication through a Data Management framework (Rucio), (2) a computing cluster supplying the processing power to run full analyses with Reana, a re-analysis software, (3) a federated and reliable Authentication and Authorization layer and (4) an enhanced notebook interface with containerised environments to hide the infrastructure's complexity from the user. The deployment of the Virtual Research Environment is open-source and modular, in order to make it easily reproducible by partner institutions; it is publicly accessible and kept up to date by taking advantage of state of the art IT-infrastructure technologies.

    image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/ CERN Document Serverarrow_drop_down
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    CERN Document Server
    Other literature type . 2023
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    https://doi.org/10.48550/arxiv...
    Article . 2023
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      CERN Document Server
      Other literature type . 2023
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      https://doi.org/10.48550/arxiv...
      Article . 2023
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    Authors: Labropoulou, Penny; Lindemann, David;

    The presentation was held during the Mutual Learning Workshop for Improving Cultural Heritage Bibliographical Data (October 12-14, 2022) organised by the Bibliographical Data Working Group of the DARIAH-ERIC. The Mutual Learning Workshop for Improving Cultural Heritage Bibliographical Data has been supported by the DARIAH ERIC.

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    ZENODO
    Other literature type . 2022
    License: CC BY
    Data sources: ZENODO
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    ZENODO
    Presentation . 2022
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      ZENODO
      Other literature type . 2022
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      Presentation . 2022
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    Authors: Hannes Berg; Maria A. Wirtz Martin; Nadide Altincekic; Islam Alshamleh; +79 Authors

    Work at BMRZ is supported by the state of Hesse. Work in Covid19-NMR was supported by the Goethe Corona Funds, by the IWBEFRE-program 20007375 of state of Hesse, the DFG through CRC902: “Molecular Principles of RNA-based regulation.” and through infrastructure funds (project numbers: 277478796, 277479031, 392682309, 452632086, 70653611) and by European Union’s Horizon 2020 research and innovation program iNEXT-discovery under grant agreement No 871037. BY-COVID receives funding from the European Union’s Horizon Europe Research and Innovation Programme under grant agreement number 101046203. “INSPIRED” (MIS 5002550) project, implemented under the Action “Reinforcement of the Research and Innovation Infrastructure,” funded by the Operational Program “Competitiveness, Entrepreneurship and Innovation” (NSRF 2014–2020) and co-financed by Greece and the EU (European Regional Development Fund) and the FP7 REGPOT CT-2011-285950—“SEE-DRUG” project (purchase of UPAT’s 700 MHz NMR equipment). The support of the CERM/CIRMMP center of Instruct-ERIC is gratefully acknowledged. This work has been funded in part by a grant of the Italian Ministry of University and Research (FISR2020IP_02112, ID-COVID) and by Fondazione CR Firenze. A.S. is supported by the Deutsche Forschungsgemeinschaft [SFB902/B16, SCHL2062/2-1] and the Johanna Quandt Young Academy at Goethe [2019/AS01]. M.H. and C.F. thank SFB902 and the Stiftung Polytechnische Gesellschaft for the Scholarship. L.L. work was supported by the French National Research Agency (ANR, NMR-SCoV2-ORF8), the Fondation de la Recherche Médicale (FRM, NMR-SCoV2-ORF8), FINOVI and the IR-RMN-THC Fr3050 CNRS. Work at UConn Health was supported by grants from the US National Institutes of Health (R01 GM135592 to B.H., P41 GM111135 and R01 GM123249 to J.C.H.) and the US National Science Foundation (DBI 2030601 to J.C.H.). Latvian Council of Science Grant No. VPP-COVID-2020/1-0014. National Science Foundation EAGER MCB-2031269. This work was supported by the grant Krebsliga KFS-4903-08-2019 and SNF-311030_192646 to J.O. P.G. (ITMP) The EOSC Future project is co-funded by the European Union Horizon Programme call INFRAEOSC-03-2020—Grant Agreement Number 101017536. Open Access funding enabled and organized by Projekt DEAL SARS-CoV-2 (SCoV2) and its variants of concern pose serious challenges to the public health. The variants increased challenges to vaccines, thus necessitating for development of new intervention strategies including anti-virals. Within the international Covid19-NMR consortium, we have identified binders targeting the RNA genome of SCoV2. We established protocols for the production and NMR characterization of more than 80 % of all SCoV2 proteins. Here, we performed an NMR screening using a fragment library for binding to 25 SCoV2 proteins and identified hits also against previously unexplored SCoV2 proteins. Computational mapping was used to predict binding sites and identify functional moieties (chemotypes) of the ligands occupying these pockets. Striking consensus was observed between NMR-detected binding sites of the main protease and the computational procedure. Our investigation provides novel structural and chemical space for structure-based drug design against the SCoV2 proteome. 12 pags., 4 figs., 3 tabs. Peer reviewed

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    Authors: Dritsou, Vicky; Ilvanidou, Maria; Despotidou, Isidora; Liakopoulou, Vicky; +2 Authors

    Humanities researchers often need to study heterogeneous digitized archives from different sources. But how can they deal with this heterogeneity, both in terms of structure and semantics? What are the digital tools they can use in order to integrate resources and study them as a whole? And what if they are unfamiliar with the methods and tools available? Towards this end, DARIAH-EU[1] and CLARIN[2] research infrastructures already support researchers in exploiting digital tools. Specific use case research scenarios have also been developed, with the PARTHENOS SSK[3] being a successful example. In this paper we describe our related (ongoing) experience from the development of the Greek research infrastructure APOLLONIS[4], where, among others, we have focused on identifying and supporting the workflows that researchers need to follow to perform specific research studies while jointly accessing disparate archives. Using the decade of 1940s as a use case, a turbulent period in Greek history due to its significant events (WWII, Occupation, Opposition, Liberation, Civil War), we have assembled (digitized) historical archives, coming from different providers and shedding light on different historical aspects of these events. From the acquisition of the resources to the desired outcome, we record the workflows of the whole research study, including the initial curation process of the digitized archives, the ingestion, the joint indexing of the data, the generation of semantic graph representations and, finally, their publication and searching. After the acquisition of the heterogeneous source materials we perform a detailed investigation of their structure and contents, in order to map the different archive metadata onto a common metadata schema, thus enabling joint indexing and establishing semantic relations among the contents of the archives. The next step is data cleaning, where messy records are cleaned and normalized. Natural Language Processing methods are then exploited for the extraction of additional information contained in the archival records or in free text metadata fields, such as persons, places, armed units, dates and topics, which enhance the initial datasets. The outcome is encoded in XML using the common schema and ingested into a repository through an aggregator implemented using the MoRE[5] system. A joint index based on a set of basic criteria is generated and maintained, thus ensuring joint access to all archival records regardless of their source. In addition, an RDF representation is generated from the encoded archival data, enabling their publication in the form of a semantic graph and supporting interesting complex queries. This is based on a specifically designed extension of CIDOC CRM[6] and a compilation of a list of research queries of varying complexity encoded in SPARQL. Preliminary tests of the entire workflows and the tools used in all steps yielded very encouraging results. Our immediate plans include full scale ingestion and indexing of the material from a number of archives, producing the corresponding semantic graph and streamlining the incorporation of new archives. [1]DARIAH-EU, https://www.dariah.eu/ [2]CLARIN, https://www.clarin.eu/ [3]PARTHENOS Standardization Survival Kit (SSK), http://www.parthenos-project.eu/portal/ssk-2 [4]APOLLONIS Greek Infrastructure for Digital Arts, Humanities and Language Research and Innovation, https://apollonis-infrastructure.gr/ [5]MoRE Aggregator, http://more.dcu.gr/ [6]CIDOC CRM, http://www.cidoc-crm.org/

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    Authors: Gazzarrini, Elena; Garcia, Enrique; Gosein, Domenic; Moya, Alba Vendrell; +2 Authors

    The Virtual Research Environment is an analysis platform developed at CERN serving the needs of scientific communities involved in European Projects. Its scope is to facilitate the development of end-to-end physics workflows, providing researchers with access to an infrastructure and to the digital content necessary to produce and preserve a scientific result in compliance with FAIR principles. The platform's development is aimed at demonstrating how sciences spanning from High Energy Physics to Astrophysics could benefit from the usage of common technologies, initially born to satisfy CERN's exabyte-scale data management needs. The Virtual Research Environment's main components are (1) a federated distributed storage solution (the Data Lake), providing functionalities for data injection and replication through a Data Management framework (Rucio), (2) a computing cluster supplying the processing power to run full analyses with Reana, a re-analysis software, (3) a federated and reliable Authentication and Authorization layer and (4) an enhanced notebook interface with containerised environments to hide the infrastructure's complexity from the user. The deployment of the Virtual Research Environment is open-source and modular, in order to make it easily reproducible by partner institutions; it is publicly accessible and kept up to date by taking advantage of state of the art IT-infrastructure technologies.

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    https://doi.org/10.48550/arxiv...
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    Authors: Labropoulou, Penny; Lindemann, David;

    The presentation was held during the Mutual Learning Workshop for Improving Cultural Heritage Bibliographical Data (October 12-14, 2022) organised by the Bibliographical Data Working Group of the DARIAH-ERIC. The Mutual Learning Workshop for Improving Cultural Heritage Bibliographical Data has been supported by the DARIAH ERIC.

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