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1687 Publications visible to you, out of a total of 1687
Bringing Communities Together: Mapping the Investigation-Study-Assay-Model (ISA) to Fast Healthcare Interoperability Resources (FHIR).

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

Scalable stellar evolution forecasting — Deep learning emulation versus hierarchical nearest-neighbor interpolation

Abstract

Not specified

Authors: K. Maltsev, F. R. N. Schneider, F. K. Röpke, A. I. Jordan, G. A. Qadir, W. E. Kerzendorf, K. Riedmiller, P. van der Smagt

Date Published: 19th Jan 2024

Publication Type: Journal

Accelerated chemical science with AI

Abstract (Expand)

The ASLLA Symposium focused on accelerating chemical science with AI. Discussions on data, new applications, algorithms, and education were summarized. Recommendations for researchers, educators, and …educators, and academic bodies were provided.

Authors: Seoin Back, Alán Aspuru-Guzik, Michele Ceriotti, Ganna Gryn'ova, Bartosz Grzybowski, Geun Ho Gu, Jason Hein, Kedar Hippalgaonkar, Rodrigo Hormázabal, Yousung Jung, Seonah Kim, Woo Youn Kim, Seyed Mohamad Moosavi, Juhwan Noh, Changyoung Park, Joshua Schrier, Philippe Schwaller, Koji Tsuda, Tejs Vegge, O. Anatole von Lilienfeld, Aron Walsh

Date Published: 17th Jan 2024

Publication Type: Journal

Standardization landscape, needs and gaps for the virtual human twin (VHT)

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

EDITH standards implementation guide (IG)

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 the …he 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

Substituting density functional theory in reaction barrier calculations for hydrogen atom transfer in proteins

Abstract (Expand)

Hydrogen atom transfer (HAT) reactions are important in many biological systems. As these reactions are hard to observe experimentally, it is of high interest to shed light on them using simulations. … Here, we present a machine learning model based on graph neural networks for the prediction of energy barriers of HAT reactions in proteins. As input, the model uses exclusively non-optimized structures as obtained from classical simulations. It was trained on more than 17 000 energy barriers calculated using hybrid density functional theory. We built and evaluated the model in the context of HAT in collagen, but we show that the same workflow can easily be applied to HAT reactions in other biological or synthetic polymers. We obtain for relevant reactions (small reaction distances) a model with good predictive power (R2 ∼ 0.9 and mean absolute error of <3 kcal mol−1). As the inference speed is high, this model enables evaluations of dozens of chemical situations within seconds. When combined with molecular dynamics in a kinetic Monte-Carlo scheme, the model paves the way toward reactive simulations.

Authors: Kai Riedmiller, Patrick Reiser, Elizaveta Bobkova, Kiril Maltsev, Ganna Gryn'ova, Pascal Friederich, Frauke Gräter

Date Published: 16th Jan 2024

Publication Type: Journal

Substituting density functional theory in reaction barrier calculations for hydrogen atom transfer in proteins

Abstract (Expand)

Hydrogen atom transfer (HAT) reactions are important in many biological systems. As these reactions are hard to observe experimentally, it is of high interest to shed light on them using simulations. … Here, we present a machine learning model based on graph neural networks for the prediction of energy barriers of HAT reactions in proteins. As input, the model uses exclusively non-optimized structures as obtained from classical simulations. It was trained on more than 17 000 energy barriers calculated using hybrid density functional theory. We built and evaluated the model in the context of HAT in collagen, but we show that the same workflow can easily be applied to HAT reactions in other biological or synthetic polymers. We obtain for relevant reactions (small reaction distances) a model with good predictive power (R2 ∼ 0.9 and mean absolute error of <3 kcal mol−1). As the inference speed is high, this model enables evaluations of dozens of chemical situations within seconds. When combined with molecular dynamics in a kinetic Monte-Carlo scheme, the model paves the way toward reactive simulations.

Authors: Kai Riedmiller, Patrick Reiser, Elizaveta Bobkova, Kiril Maltsev, Ganna Gryn’ova, Pascal Friederich, Frauke Gräter

Date Published: 16th Jan 2024

Publication Type: Journal

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