Publications

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57 Publications visible to you, out of a total of 57

Abstract (Expand)

The Metadata Schema of the NFDI4Health and the NFDI4Health Task Force COVID-19 (Metadata Schema) 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_1 of the Metadata Schema, which introduces two new resource types, namely registries and secondary data sources. Accordingly, the metadata set describing studies, which was part of the core module in previous versions, has been split into a separate module and adapted to also apply to registries and secondary data sources. An additional use case-specific module has also been added, including metadata specific to record linkage. The undertaken changes are described within the document.

Authors: Haitham Abaza, A. Shutsko, M. Golebiewski, Sophie Klopfenstein, C. O. Schmidt, Carina Vorisek, NFDI4Health Task Force COVID-19, NFDI4Health, C. Brünings-Kuppe, V. Clemens, J. Darms, S. Hanß, T. Intemann, F. Jannasch, E. Kasbohm, B. Lindstadt, M. Lobe, E. Orban, I. Perrar, M. Peters, U. Sax, M. Schulze, C. Schupp, F. Schwarz, C. Schwedhelm, S. Strathmann, D. Waltemath, H. Wünsche, A. A. Zeleke

Date Published: 10th May 2023

Publication Type: Misc

Abstract (Expand)

Open and practical exchange, dissemination, and reuse of specimens and data have become a fundamental requirement for life sciences research. The quality of the data obtained and thus the findings and knowledge derived is thus significantly influenced by the quality of the samples, the experimental methods, and the data analysis. Therefore, a comprehensive and precise documentation of the pre-analytical conditions, the analytical procedures, and the data processing are essential to be able to assess the validity of the research results. With the increasing importance of the exchange, reuse, and sharing of data and samples, procedures are required that enable cross-organizational documentation, traceability, and non-repudiation. At present, this information on the provenance of samples and data is mostly either sparse, incomplete, or incoherent. Since there is no uniform framework, this information is usually only provided within the organization and not interoperably. At the same time, the collection and sharing of biological and environmental specimens increasingly require definition and documentation of benefit sharing and compliance to regulatory requirements rather than consideration of pure scientific needs. In this publication, we present an ongoing standardization effort to provide trustworthy machine-actionable documentation of the data lineage and specimens. We would like to invite experts from the biotechnology and biomedical fields to further contribute to the standard.

Authors: Rudolf Wittner, Petr Holub, Cecilia Mascia, Francesca Frexia, Heimo Müller, Markus Plass, Clare Allocca, Fay Betsou, Tony Burdett, Ibon Cancio, Adriane Chapman, Martin Chapman, Mélanie Courtot, Vasa Curcin, Johann Eder, Mark Elliot, Katrina Exter, Carole Goble, Martin Golebiewski, Bron Kisler, Andreas Kremer, Simone Leo, Sheng Lin‐Gibson, Anna Marsano, Marco Mattavelli, Josh Moore, Hiroki Nakae, Isabelle Perseil, Ayat Salman, James Sluka, Stian Soiland‐Reyes, Caterina Strambio‐De‐Castillia, Michael Sussman, Jason R. Swedlow, Kurt Zatloukal, Jörg Geiger

Date Published: 18th Apr 2023

Publication Type: Journal

Abstract (Expand)

This special issue of the Journal of Integrative Bioinformatics contains updated specifications of COMBINE standards in systems and synthetic biology. The 2022 special issue presents three updates to the standards: CellML 2.0.1, SBML Level 3 Package: Spatial Processes, Version 1, Release 1, and Synthetic Biology Open Language (SBOL) Version 3.1.0. This document can also be used to identify the latest specifications for all COMBINE standards. In addition, this editorial provides a brief overview of the COMBINE 2022 meeting in Berlin.

Authors: M. Konig, P. Gleeson, M. Golebiewski, T. E. Gorochowski, M. Hucka, S. M. Keating, C. J. Myers, D. P. Nickerson, B. Sommer, D. Waltemath, F. Schreiber

Date Published: 1st Mar 2023

Publication Type: Journal

Abstract (Expand)

Abstract 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-hostribing SARS-CoV-2-host interactions and develop interoperable bioinformatic pipelines for novel target identification and drug repurposing. Community-driven and highly interdisciplinary, the project is collaborative and supports community standards, open access, and the FAIR data principles. The coordination of community work allowed for an impressive step forward in building interfaces between Systems Biology tools and platforms. Our framework links key molecules highlighted from broad omics data analysis and computational modeling to dysregulated pathways in a cell-, tissue- or patient-specific manner. We also employ text mining and AI-assisted analysis to identify potential drugs and drug targets and use topological analysis to reveal interesting structural features of the map. The proposed framework is versatile and expandable, offering a significant upgrade in the arsenal used to understand virus-host interactions and other complex pathologies.

Authors: Anna Niarakis, Marek Ostaszewski, Alexander Mazein, Inna Kuperstein, Martina Kutmon, Marc E. Gillespie, Akira Funahashi, Marcio Luis Acencio, Ahmed Hemedan, Michael Aichem, Karsten Klein, Tobias Czauderna, Felicia Burtscher, Takahiro G. Yamada, Yusuke Hiki, Noriko F. Hiroi, Finterly Hu, Nhung Pham, Friederike Ehrhart, Egon L. Willighagen, Alberto Valdeolivas, Aurelien Dugourd, Francesco Messina, Marina Esteban-Medina, Maria Peña-Chilet, Kinza Rian, Sylvain Soliman, Sara Sadat Aghamiri, Bhanwar Lal Puniya, Aurélien Naldi, Tomáš Helikar, Vidisha Singh, Marco Fariñas Fernández, Viviam Bermudez, Eirini Tsirvouli, Arnau Montagud, Vincent Noël, Miguel Ponce de Leon, Dieter Maier, Angela Bauch, Benjamin M. Gyori, John A. Bachman, Augustin Luna, Janet Pinero, Laura I. Furlong, Irina Balaur, Adrien Rougny, Yohan Jarosz, Rupert W. Overall, Robert Phair, Livia Perfetto, Lisa Matthews, Devasahayam Arokia Balaya Rex, Marija Orlic-Milacic, Monraz Gomez Luis Cristobal, Bertrand De Meulder, Jean Marie Ravel, Bijay Jassal, Venkata Satagopam, Guanming Wu, Martin Golebiewski, Piotr Gawron, Laurence Calzone, Jacques S. Beckmann, Chris T. Evelo, Peter D’Eustachio, Falk Schreiber, Julio Saez-Rodriguez, Joaquin Dopazo, Martin Kuiper, Alfonso Valencia, Olaf Wolkenhauer, Hiroaki Kitano, Emmanuel Barillot, Charles Auffray, Rudi Balling, Reinhard Schneider

Date Published: 19th Dec 2022

Publication Type: Misc

Abstract (Expand)

The report focusses on national and EU-case studies (good practice examples) for integrating patient derived data, such as phenotype and large scale data, for in silico modelling in personalized medicine.Not specified

Authors: Martin Golebiewski, Marc Kirschner, Sylvia Krobitsch, EU-STANDS4PM consortium

Date Published: 15th Dec 2022

Publication Type: Tech report

Abstract (Expand)

This document specifies requirements for the consistent formatting and documentation of data and corresponding metadata (i.e. data describing the data and its context) in the life sciences, including biotechnology, and biomedical, as well as non-human biological research and development. It provides guidance on rendering data in the life sciences findable, accessible, interoperable and reusable (F-A-I-R). This document is applicable to manual or computational workflows that systematically capture, record or integrate data and corresponding metadata in the life sciences for other purposes. This document provides formatting requirements for both primary experimental or procedural data obtained manually and machine derived data. This document also describes requirements for storing, sharing, accessing, interoperability and reuse of data and corresponding metadata in the life sciences. This document specifies requirements for large quantities of data systematically obtained from automated high throughput workflows in the life sciences, as well as requirements for large-scale and small-scale data sets obtained by other life science technologies and manual data capture. This document is applicable to many domains in biotechnology and the life sciences including, but not limited to: basic/applied research in all domains of the life sciences, and industrial, medical, agricultural, or environmental biotechnology (excluding for diagnostic or therapeutic purposes), as well as methodology-driven domains, such as genomics (including massive parallel sequencing, metagenomics, epigenomics and functional genomics), transcriptomics, translatomics, proteomics, metabolomics, lipidomics, glycomics, enzymology, immunochemistry, synthetic biology, systems biology, systems medicine and related fields.

Author: Martin Golebiewski

Date Published: 4th Nov 2022

Publication Type: Manual

Abstract

Not specified

Authors: Birte Lindstädt, Aliaksandra Shutsko, Martin Golebiewski, Dennis-Kenji Kipker, Vanessa Lettieri, Sophie Klopfenstein, Carina Vorisek, Matthias Löbe, Carsten Oliver Schmidt

Date Published: 11th Feb 2022

Publication Type: Manual

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