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Making Epidemiological and Clinical Studies FAIR Using the Example of COVID-19

Abstract (Expand)

Abstract FAIRification of personal health data is of utmost importance to improve health research and political as well as medical decision-making, which ultimately contributes to a better health of …utes to a better health of the general population. Despite the many advances in information technology, several obstacles such as interoperability problems remain and relevant research on the health topic of interest is likely to be missed out due to time-consuming search and access processes. A recent example is the COVID-19 pandemic, where a better understanding of the virus’ transmission dynamics as well as preventive and therapeutic options would have improved public health and medical decision-making. Consequently, the NFDI4Health Task Force COVID-19 was established to foster the FAIRification of German COVID-19 studies. This paper describes the various steps that have been taken to create low barrier workflows for scientists in finding and accessing German COVID-19 research. It provides an overview on the building blocks for FAIR health research within the Task Force COVID-19 and how this initial work was subsequently expanded by the German consortium National Research Data Infrastructure for Personal Health Data (NFDI4Health) to cover a wider range of studies and research areas in epidemiological, public health and clinical research. Lessons learned from the Task Force helped to improve the respective tasks of NFDI4Health.

Authors: Iris Pigeot, Wolfgang Ahrens, Johannes Darms, Juliane Fluck, Martin Golebiewski, Horst K. Hahn, Xiaoming Hu, Timm Intemann, Elisa Kasbohm, Toralf Kirsten, Sebastian Klammt, Sophie Anne Ines Klopfenstein, Bianca Lassen-Schmidt, Manuela Peters, Ulrich Sax, Dagmar Waltemath, Carsten Oliver Schmidt

Date Published: 1st Jul 2024

Publication Type: Journal

Jet formation in stellar interactions

Abstract

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Author: Friedrich Röpke

Date Published: 1st Jul 2024

Publication Type: InProceedings

Computational Approaches for Integrating out Subjectivity in Cognate Synonym Selection

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Working with cognate data involves handling synonyms, that is, multiple words that describe the same concept in a language. In the early days of language phylogenetics it was recommended to select one … synonym only. However, as we show here, binary character matrices, which are used as input for computational methods, do allow for representing the entire dataset including all synonyms. Here we address the question how one can and if one should include all synonyms or whether it is preferable to select synonyms a priori. To this end, we perform maximum likelihood tree inferences with the widely used RAxML-NG tool and show that it yields plausible trees when all synonyms are used as input. Furthermore, we show that a priori synonym selection can yield topologically substantially different trees and we therefore advise against doing so. To represent cognate data including all synonyms, we introduce two types of character matrices beyond the standard binary ones: probabilistic binary and probabilistic multi-valued character matrices. We further show that it is dataset-dependent for which character matrix type the inferred RAxML-NG tree is topologically closest to the gold standard. We also make available a Python interface for generating all of the above character matrix types for cognate data provided in CLDF format.

Authors: Luise Häuser, Gerhard Jäger, Alexandros Stamatakis

Date Published: 28th Jun 2024

Publication Type: Proceedings

Structural bioinformatics approach to exploring transient binding pockets in proteins, (Bachelor's Thesis), Biochemistry, Faculty of Biosciences and Faculty of Chemistry and Earth Sciences, Ruprecht-Karls University, Heidelberg

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Editor:

Date Published: 21st Jun 2024

Publication Type: Bachelor's Thesis

Brief Announcement: (Near) Zero-Overhead C++ Bindings for MPI

Abstract (Expand)

The Message-Passing Interface (MPI) and C++ form the backbone of high-performance computing and algorithmic research in the field of distributed-memory computing, but MPI only provides C and Fortran … bindings. This provides good language interoperability, but higher-level programming languages make development quicker and less error-prone. We propose novel C++ language bindings designed to cover the whole range of abstraction levels from low-level MPI calls to convenient STL-style bindings, where most parameters are inferred from a small subset of the full parameter set. This allows for both rapid prototyping and fine-tuning of distributed code with predictable runtime behavior and memory management. Using template-metaprogramming, only code paths required for computing missing parameters are generated at compile time, which results in (near) zero-overhead bindings.

Authors: Kunal Agrawal, Erez Petrank, Demian Hespe, Lukas Hübner, Florian Kurpicz, Peter Sanders, Matthias Schimek, Daniel Seemaier, Tim Niklas Uhl

Date Published: 17th Jun 2024

Publication Type: Proceedings

What causes the failure of explicit to implicit discourse relation recognition?

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Authors: Wei Liu, Stephen Wan, Michael Strube

Date Published: 16th Jun 2024

Publication Type: InProceedings

Increasing Detection Rate for Imbalanced Malicious Traffic using Generative Adversarial Networks

Abstract

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Authors: Pascal Memmesheimer, Stefan Machmeier, Vincent Heuveline

Date Published: 5th Jun 2024

Publication Type: Journal

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