Publications

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115 Publications visible to you, out of a total of 115

Abstract (Expand)

INTRODUCTION: The COVID-19 Disease Map project is a large-scale community effort uniting 277 scientists from 130 Institutions around the globe. We use high-quality, mechanistic content describing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. METHODS: Extensive community work allowed an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework can link biomolecules from omics data analysis and computational modelling to dysregulated pathways in a cell-, tissue- or patient-specific manner. Drug repurposing using text mining and AI-assisted analysis identified potential drugs, chemicals and microRNAs that could target the identified key factors. RESULTS: Results revealed drugs already tested for anti-COVID-19 efficacy, providing a mechanistic context for their mode of action, and drugs already in clinical trials for treating other diseases, never tested against COVID-19. DISCUSSION: The key advance is that the proposed framework is versatile and expandable, offering a significant upgrade in the arsenal for virus-host interactions and other complex pathologies.

Authors: A. Niarakis, M. Ostaszewski, A. Mazein, I. Kuperstein, M. Kutmon, M. E. Gillespie, A. Funahashi, M. L. Acencio, A. Hemedan, M. Aichem, K. Klein, T. Czauderna, F. Burtscher, T. G. Yamada, Y. Hiki, N. F. Hiroi, F. Hu, N. Pham, F. Ehrhart, E. L. Willighagen, A. Valdeolivas, A. Dugourd, F. Messina, M. Esteban-Medina, M. Pena-Chilet, K. Rian, S. Soliman, S. S. Aghamiri, B. L. Puniya, A. Naldi, T. Helikar, V. Singh, M. F. Fernandez, V. Bermudez, E. Tsirvouli, A. Montagud, V. Noel, M. Ponce-de-Leon, D. Maier, A. Bauch, B. M. Gyori, J. A. Bachman, A. Luna, J. Pinero, L. I. Furlong, I. Balaur, A. Rougny, Y. Jarosz, R. W. Overall, R. Phair, L. Perfetto, L. Matthews, D. A. B. Rex, M. Orlic-Milacic, L. C. M. Gomez, B. De Meulder, J. M. Ravel, B. Jassal, V. Satagopam, G. Wu, M. Golebiewski, P. Gawron, L. Calzone, J. S. Beckmann, C. T. Evelo, P. D'Eustachio, F. Schreiber, J. Saez-Rodriguez, J. Dopazo, M. Kuiper, A. Valencia, O. Wolkenhauer, H. Kitano, E. Barillot, C. Auffray, R. Balling, R. Schneider

Date Published: 29th Feb 2024

Publication Type: Journal

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)

Adhering to FAIR principles (findability, accessibility, interoperability, reusability) ensures sustainability and reliable exchange of data and metadata. Research communities need common infrastructures and information models to collect, store, manage and work with data and metadata. The German initiative NFDI4Health created a metadata schema and an infrastructure integrating existing platforms based on different information models and standards. To ensure system compatibility and enhance data integration possibilities, we mapped the Investigation-Study-Assay (ISA) model to Fast Healthcare Interoperability Resources (FHIR). We present the mapping in FHIR logical models, a resulting FHIR resources' network and challenges that we encountered. Challenges mainly related to ISA's genericness, and to different structures and datatypes used in ISA and FHIR. Mapping ISA to FHIR is feasible but requires further analyses of example data and adaptations to better specify target FHIR elements, and enable possible automatized conversions from ISA to FHIR.

Authors: S. A. I. Klopfenstein, J. Sass, C. N. Vorisek, F. Jorczik, C. O. Schmidt, M. Lobe, M. Golebiewski, H. Abaza, S. Thun

Date Published: 25th Jan 2024

Publication Type: Journal

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)

In systems biology and systems medicine data of many different types and obtained from manifold methods are used to set up computational models for simulations and predictions. These data need to be interoperable to integrate them into the models or use them for model validation. To achieve this, standards are crucial for structuring, describing, and associating models and data, as well as their respective parts, graphical visualization, and information about applied experimental or computational methods. Such standards also assist with describing how constituent parts interact together, or are linked, and how they are embedded in their environmental and experimental context.

Authors: Martin Golebiewski, Gerhard Mayer

Date Published: 2024

Publication Type: InCollection

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