Publications

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103 Publications visible to you, out of a total of 103

Abstract (Expand)

As part of the BioHackathon Europe 2023, we here report on the progress of the hacking team preparing a resource index and knowledge graph based on the JSON-LD Bioschemas markup from several resourcesal resources in the life- and natural sciences, predominantly from the fields of plant- and (bio)chemistry research. This preliminary analysis will allow us to better understand how Bioschemas markup is currently used in these two communities, so we can take actions to improve guidelines and validation on the Bioschemas markup and the data providers side. The lessons learnt will be useful for other communities as well. The ultimate goal is facilitating and improving interoperability across resources.

Authors: Daniel Arend, Alessio Del Conte, Manuel Feser, Yojana Gadiya, Alban Gaignard, Leyla Jael Castro, Ivan Mičetić, Sebastien Moretti, Steffen Neumann, Noura Rayya, Ginger Tsueng, Egon Willighagen, Ulrike Wittig

Date Published: 30th Jan 2024

Publication Type: Misc

Abstract (Expand)

This document created within the European Coordination and Support Action (CSA) of the EDITH (Ecosystem Digital Twins in Healthcare) project describes the current landscape of formatting and description standards, terminologies and metadata guidelines for virtual human twins (VHTs). It refers to corresponding biomedical data, simulation models and workflows, as well as their metadata relevant for the definition, implementation, and simulation of Digital Twins in Healthcare (DTHs). It comprises both, ISO and community standards and lists the relevant standards and terminologies describing the modelling process, the integration of domain-specific medical research data with routine data from electronic health records, the documentation of data provenance, the validation process for biomedical, physiological, bio-signaling and other healthcare data and models. The document also reveals needs and gaps in the current standards landscape to drive the further development of such standards. Therefore, remarks and comments on how to improve existing standards or on areas for which standards are still missing are very welcome.

Author: Gerhard Mayer, Martin Golebiewski

Date Published: 17th Jan 2024

Publication Type: Tech report

Abstract (Expand)

This document provides a guideline for using and implementing standards, terminologies, and metadata guidelines when setting up, executing, and archiving virtual human twins. It is created within thehe European Coordination and Support Action (CSA) of the EDITH (Ecosystem Digital Twins in Healthcare) project. The aim of this implementation guide is two-fold: First it gives hints to the modelers, which steps they should follow in the model building process and which standards, terminologies, and guidelines (depending on their modelling domain) they should use in defining their biomedical and healthcare models. Second it is intended as a practical guide for implementers giving hints, which standards, terminologies, and guidelines should be supported in the long-term by the simulation environment consisting of the repository, the simulation platform, and the workflow execution engines. Initially it suffices if they support all formats and annotations used by the demonstrator use cases. To get an overview and access information on the standards, terminologies, and metadata guidelines referenced in this document, there also is an EDITH FairSharing collection available: https://fairsharing.org/4787

Author: Gerhard Mayer, Martin Golebiewski

Date Published: 17th Jan 2024

Publication Type: Tech report

Abstract (Expand)

Research data management (RDM) is central to the implementation of the FAIR (Findable Accessible, Interoperable, Reusable) and Open Science principles. Recognising the importance of RDM, ELIXIR PlatformsIXIR Platforms and Nodes have invested in RDM and launched various projects and initiatives to ensure good data management practices for scientific excellence. These projects have resulted in a rich set of tools and resources highly valuable for FAIR data management. However, these resources remain scattered across projects and ELIXIR structures, making their dissemination and application challenging. Therefore, it becomes imminent to coordinate these efforts for sustainable and harmonised RDM practices with dedicated forums for RDM professionals to exchange knowledge and share resources. The proposed ELIXIR RDM Community will bring together RDM experts to develop ELIXIR’s vision and coordinate its activities, taking advantage of the available assets. It aims to coordinate RDM best practices and illustrate how to use the existing ELIXIR RDM services. The Community will be built around three integral pillars, namely, a network of RDM professionals, RDM knowledge management and RDM training expertise and resources. It will also engage with external stakeholders to leverage benefits and provide a forum to RDM professionals for regular knowledge exchange, capacity building and development of harmonised RDM practices, keeping in line with the overall scope of the RDM Community. In the short term, the Community aims to build upon the existing resources and ensure that the content of these remain up to date and fit for purpose. In the long run, the Community will aim to strengthen the skills and knowledge of its RDM professionals to support the emerging needs of the scientific community. The Community will also devise an effective strategy to engage with other ELIXIR structures and international stakeholders to influence and align with developments and solutions in the RDM field.

Authors: Flora D'Anna, Niclas Jareborg, Mijke Jetten, Minna Ahokas, Pinar Alper, Robert Andrews, Korbinian Bösl, Teresa D’Altri, Daniel Faria, Nazeefa Fatima, Siiri Fuchs, Clare Garrard, Wei Gu, Katharina F. Heil, Yvonne Kallberg, Flavio Licciulli, Nils-Christian Lübke, Ana M. P. Melo, Ivan Mičetić, Jorge Oliveira, Anastasis Oulas, Patricia M. Palagi, Krzysztof Poterlowicz, Xenia Perez-Sitja, Patrick Ruch, Susanna-Assunta Sansone, Helena Schnitzer, Celia van Gelder, Thanasis Vergoulis, Daniel Wibberg, Ulrike Wittig, Brane Leskošek, Jiri Vondrasek, Munazah Andrabi

Date Published: 2024

Publication Type: Journal

Abstract (Expand)

Originally developed by the NFDI4Health Task Force COVID-19, the Metadata Schema of the NFDI4Health contains a list of properties that describe a resource to be registered in the German Central Health Study Hub. Currently, two main types of resources are distinguished: a) study descriptions (i.e., metadata set describing a study) and b) study documents. However, due to the generic character of the Metadata Schema, other types of resources may also be described and registered. The metadata properties are divided into mandatory and recommended ones. Along with bibliographic information such as title and description of the resource, the related persons and organizations contributing to the development of the resource can also be specified. The results of studies published in journal articles or other text publications can be linked too. For studies, information about study design and accessibility of the collected data should be additionally provided. The Metadata Schema consists mainly of properties adapted from established standards and models such as DataCite Metadata Schema 4.4, data models of the ClinicalTrials.gov, German Clinical Trials Register, International Clinical Trials Registry, HL7® FHIR, MIABIS, Maelstrom Research cataloguing toolkit and DDI Controlled Vocabularies. This is an updated version V3_3 of the Metadata Schema, which improves the modules of the previous version via refined display names, description and additional information texts, and short input helps and examples. The new version also introduces a new url item in the data sharing section for linking to data request applications. The undertaken changes are described within the document.

Authors: Haitham Abaza, A. Shutsko, Martin Golebiewski, Sophie Klopfenstein, C. O. Schmidt, Carina Vorisek, C. Brünings-Kuppe, V. Clemens, J. Darms, S. Hanß, T. Intemann, F. Jannasch, E. Kasbohm, Birte Lindstädt, Matthias Löbe, E. Orban, I. Perrar, M. Peters, U. Sax, M. Schulze, C. Schupp, F. Schwarz, C. Schwedhelm, S. Strathmann, Dagmar Waltemath, H. Wünsche, A. Zeleke

Date Published: 5th Dec 2023

Publication Type: Misc

Abstract (Expand)

Broad-spectrum anti-infective chemotherapy agents with activity against Trypanosomes, Leishmania, and Mycobacterium tuberculosis species were identified from a high-throughput phenotypic screening program of the 456 compounds belonging to the Ty-Box, an in-house industry database. Compound characterization using machine learning approaches enabled the identification and synthesis of 44 compounds with broad-spectrum antiparasitic activity and minimal toxicity against Trypanosoma brucei, Leishmania Infantum, and Trypanosoma cruzi. In vitro studies confirmed the predictive models identified in compound 40 which emerged as a new lead, featured by an innovative N-(5-pyrimidinyl)benzenesulfonamide scaffold and promising low micromolar activity against two parasites and low toxicity. Given the volume and complexity of data generated by the diverse high-throughput screening assays performed on the compounds of the Ty-Box library, the chemoinformatic and machine learning tools enabled the selection of compounds eligible for further evaluation of their biological and toxicological activities and aided in the decision-making process toward the design and optimization of the identified lead.

Authors: P. Linciano, A. Quotadamo, R. Luciani, M. Santucci, K. M. Zorn, D. H. Foil, T. R. Lane, A. Cordeiro da Silva, N. Santarem, C. B Moraes, L. Freitas-Junior, U. Wittig, W. Mueller, M. Tonelli, S. Ferrari, A. Venturelli, S. Gul, M. Kuzikov, B. Ellinger, J. Reinshagen, S. Ekins, M. P. Costi

Date Published: 3rd Nov 2023

Publication Type: Journal

Abstract (Expand)

Health data collected in clinical trials and epidemiological as well as public health studies cannot be freely published, but are valuable datasets whose subsequent use is of high importance for health research. The National Research Data Infrastructure for Personal Health Data (NFDI4Health) aims to promote the publication of such health data without compromising privacy. Based on existing international standards, NFDI4Health has established a generic information model for the description and preservation of high-level metadata describing health-related studies, covering both clinical and epidemiological studies. As an infrastructure for publishing such preservation metadata as well as more detailed representation information of study data (e.g. questionaries and data dictionaries), NFDI4Health has developed the German Central Health Study Hub. Content is either harvested from existing distributed sources or entered directly via a user interface. This metadata makes health studies more discoverable, and researchers can use the published metadata to evaluate the content of data collections, learn about access conditions and how and where to request data access. The goal of NFDI4Health is to establish interoperable and internationally accepted standards and processes for the publication of health data sets to make health data FAIR.

Authors: Juliane Fluck, Martin Golebiewski, Johannes Darms

Date Published: 7th Sep 2023

Publication Type: Proceedings

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