TY - JOUR A1 - Reidelbach, Marco A1 - Weber, Marcus A1 - Imhof, Petra T1 - Prediction of perturbed proton transfer networks JF - PLoS ONE N2 - The transfer of protons through proton translocating channels is a complex process, for which direct samplings of different protonation states and side chain conformations in a transition network calculation provide an efficient, bias-free description. In principle, a new transition network calculation is required for every unsampled change in the system of interest, e.g. an unsampled protonation state change, which is associated with significant computational costs. Transition networks void of or including an unsampled change are termed unperturbed or perturbed, respectively. Here, we present a prediction method, which is based on an extensive coarse-graining of the underlying transition networks to speed up the calculations. It uses the minimum spanning tree and a corresponding sensitivity analysis of an unperturbed transition network as initial guess and refinement parameter for the determination of an unknown, perturbed transition network. Thereby, the minimum spanning tree defines a sub-network connecting all nodes without cycles and minimal edge weight sum, while the sensitivity analysis analyzes the stability of the minimum spanning tree towards individual edge weight reductions. Using the prediction method, we are able to reduce the calculation costs in a model system by up to 80%, while important network properties are maintained in most predictions. Y1 - 2018 U6 - https://doi.org/https://doi.org/10.1371/journal.pone.0207718 VL - 13 IS - 12 SP - e0207718 EP - e0207718 ER - TY - JOUR A1 - Spahn, Viola A1 - Del Vecchio, Giovanna A1 - Labuz, Dominika A1 - Rodriguez-Gaztelumendi, Antonio A1 - Massaly, N. A1 - Temp, Julia A1 - Durmaz, Vedat A1 - Sabri, P. A1 - Reidelbach, Marco A1 - Machelska, Halina A1 - Weber, Marcus A1 - Stein, Christoph T1 - A nontoxic pain killer designed by modeling of pathological receptor conformations JF - Science Y1 - 2017 U6 - https://doi.org/10.1126/science.aai8636 VL - 355 IS - 6328 SP - 966 EP - 969 ER - TY - CHAP A1 - Igde, Sinaida A1 - Wölk, Hendrik A1 - Röblitz, Susanna A1 - Reidelbach, Marco A1 - Weber, Marcus A1 - Hartmann, Laura T1 - Identifying Multivalent Binding Kinetics of Precision Glycomacromolecules: A Kinetic Study Using kinITC T2 - Münster Symposium on Cooperative Effects 2015 - SFB 858, at Westfälische Wilhelms-Universität Münster, 2015 N2 - Multivalent sugar/protein interactions are well-known to proceed through different binding modes 1-5 which in turn can be described by their binding kinetics 3-5. This study provides additional insight into the association and dissociation reaction rates of complex multivalent sugar/protein interactions. Binding kinetics of recently introduced multivalent precision glycomacromolecules 6-8 to Concanavalin A (Con A) were studied by " kinetic Isothermal Titration Calorimetry " (kinITC) 9-11. The effect of multivalency is evaluated by comparing rate constants of glycomacromolecules obtaining the same and different valency of mannose ligands and by variation of the overall backbone properties, such as hydrophilic/ hydrophoboc. In addition, binding kinetics were studied using different conformations of Con A (homodimer vs.-tetramer) and thus a different protein valency. Our results show that precision glycomacromolecule/Con A binding proceeds non-cooperatively. Further, association and dissociation rates are mainly described by intermolecular complex formation. Together with the so-called functional valency, we can discriminate between " bound " and " unbound " states for macroscopic on-and off-rates, even for such complex glycooligomer/protein systems. By comparing e.g. a mono-to a divalent glycomacromolecule for their binding to dimeric Con A, we see a lower dissociation rate for the latter. As both bind monovalently to Con A, this is a strong indication for a statistical rebinding event. Further, there is a strong dependence of multivalent binding kinetics on the ligand density of glycomacromolecules as well as the Con A conformation and thus the overall on-and off-rates. Y1 - 2015 ER - TY - JOUR A1 - Spahn, Viola A1 - Del Vecchio, Giovanna A1 - Rodriguez-Gaztelumendi, Antonio A1 - Temp, Julia A1 - Labuz, Dominika A1 - Kloner, Michael A1 - Reidelbach, Marco A1 - Machelska, Halina A1 - Weber, Marcus A1 - Stein, Christoph T1 - Opioid receptor signaling, analgesic and side effects induced by a computationally designed pH-dependent agonist JF - Scientific Reports N2 - Novel pain killers without adverse effects are urgently needed. Y1 - 2018 VL - 8 SP - 8965 PB - Springer Nature ER - TY - THES A1 - Reidelbach, Marco T1 - Optimal Network Generation for the Simulation of Proton Transfer Processes Y1 - 2019 ER - TY - GEN A1 - Weber, Marcus A1 - Durmaz, Vedat A1 - Sabri, Peggy A1 - Reidelbach, Marco T1 - Supplementary simulation data for Science Manuscript ai8636 N2 - The simulation data has been produced by Vedat Durmaz, Peggy Sabri and Marco Reidelbach inside the "Computational Molecular Design" Group headed by Marcus Weber at Zuse-Institut Berlin, Takustr. 7, D-14195 Berlin, Germany. The file contains classical simulation data for different fentanyl derivates in the MOR binding pocket at different pHs. It also includes instruction files for quantum-chemical pKa-value estimations and a description of how we derived the pKa-values from the Gaussian09 log-files. Y1 - 2017 U6 - https://doi.org/10.12752/5.MWB.1.0 N1 - GROMACS trajectories and GAUSSIAN files of MOR and fentanyl derivates ER - TY - JOUR A1 - Marco, Reidelbach A1 - Marcus, Weber T1 - From Documentation to Discovery - MaRDMO and the MaRDI Ecosystem JF - 2nd Conference on Research Data Infrastructure (CoRDI) Y1 - 2025 U6 - https://doi.org/10.5281/zenodo.16735889 ER - TY - JOUR A1 - Fischer, Kristina A1 - Gerber, Anja A1 - Koprucki, Thomas A1 - Noback, Andres A1 - Reidelbach, Marco A1 - Schrade, Torsten A1 - Thiery, Florian T1 - Windows on Data: Federating Research Data with FAIR Digital Objects and Linked Open Data JF - 2nd Conference on Research Data Infrastructure (CoRDI) Y1 - 2025 U6 - https://doi.org/10.5281/zenodo.16736222 ER - TY - JOUR A1 - Biernacka, Katarzyna A1 - Castro, Leyla Jael A1 - Fritzsch, Bernadette A1 - Grossmann, Yves Vincent A1 - Reidelbach, Marco A1 - Struck, Alexander A1 - Lanza, Giacomo A1 - Walter, David A1 - Ulusoy, Inga T1 - From Vision to Implementation: Current Practices and Challenges of Software Management Plans in Research JF - 2nd Conference on Research Data Infrastructure (CoRDI) Y1 - 2025 U6 - https://doi.org/10.5281/zenodo.16735302 ER - TY - CHAP A1 - Schembera, Björn A1 - Wübbeling, Frank A1 - Kleikamp, Hendrik A1 - Schmidt, Burkhard A1 - Shehu, Aurela A1 - Reidelbach, Marco A1 - Biedinger, Christine A1 - Fiedler, Jochen A1 - Koprucki, Thomas A1 - Iglezakis, Dorothea A1 - Göddeke, Dominik T1 - Towards a Knowledge Graph for Models and Algorithms in Applied Mathematics T2 - Metadata and Semantic Research. MTSR 2024 N2 - Mathematical models and algorithms are an essential part of mathematical research data, as they are epistemically grounding numerical data. To make this research data FAIR, we present how two previously distinct ontologies, MathAlgoDB for algorithms and MathModDB for models, were merged and extended into a living knowledge graph as the key outcome. This was achieved by connecting the ontologies through computational tasks that correspond to algorithmic tasks. Moreover, we show how models and algorithms can be enriched with subject-specific metadata, such as matrix symmetry or model linearity, essential for defining workflows and determining suitable algorithms. Additionally, we propose controlled vocabularies to be added, along with a new class that differentiates base quantities from specific use case quantities. We illustrate the capabilities of the developed knowledge graph using two detailed examples from different application areas of applied mathematics, having already integrated over 250 research assets into the knowledge graph. Y1 - 2025 SN - 9783031819735 U6 - https://doi.org/10.1007/978-3-031-81974-2_8 SN - 1865-0929 VL - 2331 SP - 95 EP - 109 PB - Springer Nature Switzerland CY - Cham ER - TY - CHAP A1 - Schembera, Björn A1 - Wübbeling, Frank A1 - Kleikamp, Hendrik A1 - Biedinger, Christine A1 - Fiedler, Jochen A1 - Reidelbach, Marco A1 - Shehu, Aurela A1 - Schmidt, Burkhard A1 - Koprucki, Thomas A1 - Iglezakis, Dotothea A1 - Göddeke, Dominik T1 - Ontologies for Models and Algorithms in Applied Mathematics and Related Disciplines T2 - Metadata and Semantic Research - MTSR 2023 N2 - In applied mathematics and related disciplines, the modeling-simulation-optimization workflow is a prominent scheme, with mathematical models and numerical algorithms playing a crucial role. For these types of mathematical research data, the Mathematical Research Data Initiative has developed, merged and implemented ontologies and knowledge graphs. This contributes to making mathematical research data FAIR by introducing semantic technology and documenting the mathematical foundations accordingly. Using the concrete example of microfracture analysis of porous media, it is shown how the knowledge of the underlying mathematical model and the corresponding numerical algorithms for its solution can be represented by the ontologies. Y1 - 2023 U6 - https://doi.org/10.1007/978-3-031-65990-4_14 SP - 161 EP - 168 PB - Springer Nature Switzerland CY - Cham ET - Communications in Computer and Information Science ER - TY - JOUR A1 - Diederichs, Katja A1 - Krause, Celia A1 - Lemaire, Marina A1 - Reidelbach, Marco A1 - Windeck, Jürgen T1 - A Vision for Data Management Plans in the NFDI JF - ZENODO N2 - At present, data management plans (DMPs) are still often perceived as mere documents for funding agencies providing clarity on how research data will be handled during a funded project, but are not usually actively involved in the processes. However, they contain a great deal of information that can be shared automatically to facilitate active research data management (RDM) by providing metadata to research infrastructures and supporting communication between all involved stakeholders. This position paper brings together a number of ideas developed and collected during interdisciplinary workshops of the Data Management Planning Working Group (infra-dmp), which is part of the section Common Infrastructures of the National Research Data Infrastructure (NFDI) in Germany. We present our vision of a possible future role of DMPs, templates, and tools in the upcoming NFDI service architecture. Y1 - 2024 U6 - https://doi.org/10.5281/zenodo.10570653 ER - TY - CHAP A1 - Reidelbach, Marco A1 - Schembera, Björn A1 - Weber, Marcus T1 - Towards a FAIR Documentation of Workflows and Models in Applied Mathematics T2 - Mathematical Software – ICMS 2024 N2 - Modeling-Simulation-Optimization workflows play a fundamental role in applied mathematics. The Mathematical Research Data Initiative, MaRDI, responded to this by developing a FAIR and machine-interpretable template for a comprehensive documentation of such workflows. MaRDMO, a Plugin for the Research Data Management Organiser, enables scientists from diverse fields to document and publish their workflows on the MaRDI Portal seamlessly using the MaRDI template. Central to these workflows are mathematical models. MaRDI addresses them with the MathModDB ontology, offering a structured formal model description. Here, we showcase the interaction between MaRDMO and the MathModDB Knowledge Graph through an algebraic modeling workflow from the Digital Humanities. This demonstration underscores the versatility of both services beyond their original numerical domain. Y1 - 2024 U6 - https://doi.org/10.1007/978-3-031-64529-7_27 VL - 14749 SP - 254 EP - 262 PB - Springer Nature Switzerland CY - Cham ET - Lecture Notes in Computer Science ER - TY - JOUR A1 - Benner, Peter A1 - Danabalan, Renita A1 - Gödekke, Dominik A1 - Kastner, Lars A1 - Krause, Tabea A1 - Mietchen, Daniel A1 - Reidelbach, Marco A1 - Schembera, Björn A1 - Schubotz, Moritz A1 - Sinn, Rainer A1 - Tabelow, Karsten T1 - Research Data Management Planning in Mathematics N2 - Research data are crucial in mathematics and all scientific disciplines, as they form the foundation for empirical evidence, by enabling the validation and reproducibility of scientific findings. Mathematical research data (MathRD) have become vast and complex, and their interdisciplinary potential and abstract nature make them ubiquitous in various scientific fields. The volume of data and the velocity of its creation are rapidly increasing due to advancements in data science and computing power. This complexity extends to other disciplines, resulting in diverse research data and computational models. Thus, proper handling of research data is crucial both within mathematics and for its manifold connections and exchange with other disciplines. The National Research Data Infrastructure (NFDI), funded by the federal and state governments of Germany, consists of discipline-oriented consortia, including the Mathematical Research Data Initiative (MaRDI). MaRDI has been established to develop services, guidelines and outreach measures for all aspects of MathRD, and thus support the mathematical research community. Research data management (RDM) should be an integral component of every scientific project, and is becoming a mandatory component of grants with funding bodies such as the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation). At the core of RDM are the FAIR (Findable, Accessible, Interoperable, and Reusable) principles. This document aims to guide mathematicians and researchers from related disciplines who create RDM plans. It highlights the benefits and opportunities of RDM in mathematics and interdisciplinary studies, showcases examples of diverse MathRD, and suggests technical solutions that meet the requirements of funding agencies with specific examples. The document is regularly updated to reflect the latest developments within the mathematical community represented by MaRDI. Y1 - 2023 U6 - https://doi.org/10.5281/zenodo.10018245 ER - TY - JOUR A1 - Reidelbach, Marco A1 - Ferrer, Eloi A1 - Weber, Marcus T1 - MaRDMO Plugin BT - Document and Retrieve Workflows Using the MaRDI Portal JF - Proceedings of the Conference on Research Data Infrastructure N2 - MaRDMO, a plugin for the Research Data Management Organiser, was developed in the Mathematical Research Data Initiative to document interdisciplinary workflows using a standardised scheme. Interdisciplinary workflows recorded this way are published directly on the MaRDI portal. In addition, central information is integrated into the MaRDI knowledge graph. Next to the documentation, MaRDMO offers the possibility to retrieve existing interdisciplinary workflows from the MaRDI Knowledge Graph to allow the reproduction of the initial work and to provide scientists with new researchimpulses. Thus, MaRDMO creates a community-driven knowledge loop that could help to overcome the replication crisis. Y1 - 2023 U6 - https://doi.org/10.52825/cordi.v1i.254 SN - 2941-296X VL - 1 PB - TIB Open Publishing ER - TY - JOUR A1 - Schembera, Björn A1 - Wübbeling, Frank A1 - Koprucki, Thomas A1 - Biedinger, Christine A1 - Reidelbach, Marco A1 - Schmidt, Burkhard A1 - Göddeke, Dominik A1 - Fiedler, Jochen T1 - Building Ontologies and Knowledge Graphs for Mathematics and its Applications JF - Proceedings of the Conference on Research Data Infrastructure N2 - Ontologies and knowledge graphs for mathematical algorithms and models are presented, that have been developed by the Mathematical Research Data Initiative. This enables FAIR data handling in mathematics and the applied disciplines. Moreover, challenges of harmonization during the ontology development are discussed. Y1 - 2023 U6 - https://doi.org/10.52825/cordi.v1i.255 SN - 2941-296X VL - 1 PB - TIB Open Publishing ER - TY - JOUR A1 - Boege, Tobias A1 - Fritze, René A1 - Görgen, Christiane A1 - Hanselmann, Jeroen A1 - Iglezakis, Dorothea A1 - Kastner, Lars A1 - Koprucki, Thomas A1 - Krause, Tabea A1 - Lehrenfeld, Christoph A1 - Polla, Silvia A1 - Reidelbach, Marco A1 - Riedel, Christian A1 - Saak, Jens A1 - Schembera, Björn A1 - Tabelow, Karsten A1 - Weber, Marcus T1 - Research-Data Management Planning in the German Mathematical Community JF - Eur. Math. Soc. Mag. N2 - In this paper we discuss the notion of research data for the field of mathematics and report on the status quo of research-data management and planning. A number of decentralized approaches are presented and compared to needs and challenges faced in three use cases from different mathematical subdisciplines. We highlight the importance of tailoring research-data management plans to mathematicians’ research processes and discuss their usage all along the data life cycle. Y1 - 2023 U6 - https://doi.org/10.4171/mag/152 VL - 130 SP - 40 EP - 47 ER - TY - JOUR A1 - Reidelbach, Marco A1 - Bai, Mei A1 - Zöllner, Martin Sebastian A1 - Schneeberger, Michaela A1 - Kubicek, Katharina A1 - Kirchberg, Henning A1 - Bressler, Christian A1 - Thorwart, Michael A1 - Herrmann, Carmen T1 - Solvent dynamics of aqueous halides before and after photoionization JF - Journal of Physical Chemistry Y1 - 2022 ER - TY - GEN A1 - Reidelbach, Marco A1 - Weber, Marcus T1 - MaRDI - The mathematical Research Data Initiative T2 - Aktionstag Forschungsdaten Y1 - 2022 U6 - https://doi.org/10.5281/zenodo.7397588 ER - TY - JOUR A1 - Marco, Reidelbach T1 - MaRDMO: Future Gateway to FAIR Mathematical Data JF - E-Science-Tage 2025: Research Data Management: Challenges in a Changing World N2 - Mathematical research data plays a crucial role across scientific disciplines, yet its documentation and dissemination remain challenging due to the lack of standardized research data management practices. The MaRDMO Plugin addresses these challenges by integrating mathematical models, algorithms, and interdisciplinary workflows into the established framework of the Research Data Management Organiser (RDMO). Built on FAIR principles, MaRDMO enables structured documentation and retrieval of mathematical research data through guided questionnaires. It connects to multiple knowledge graphs, including MathModDB, MathAlgoDB, and the MaRDI Portal. Users can document and search for models, algorithms, and workflows via dynamic selection interfaces that also leverage other sources such as Wikidata. The plugin facilitates the export to the individual MaRDI services, ensuring data quality through automated validation. By embedding mathematical research data management into the widely adopted RDMO platform, MaRDMO represents a significant step toward making mathematical research data more findable, accessible, and reusable. Y1 - 2025 U6 - https://doi.org/10.11588/heibooks.1652.c23913 SP - 40 EP - 53 ER -