Publications

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1687 Publications visible to you, out of a total of 1687

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Author: Michelle Emmert

Date Published: 2022

Publication Type: Bachelor's Thesis

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Author: Anton Hanke

Date Published: 2022

Publication Type: Master's Thesis

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Author: Ainara Claveras Cabezudo

Date Published: 2022

Publication Type: Master's Thesis

Abstract (Expand)

Branched Optimal Transport (BOT) is a generalization of optimal transport in which transportation costs along an edge are subadditive. This subadditivity models an increase in transport efficiency when shipping mass along the same route, favoring branched transportation networks. We here study the NP-hard optimization of BOT networks connecting a finite number of sources and sinks in ℝ2. First, we show how to efficiently find the best geometry of a BOT network for many sources and sinks, given a topology. Second, we argue that a topology with more than three edges meeting at a branching point is never optimal. Third, we show that the results obtained for the Euclidean plane generalize directly to optimal transportation networks on two-dimensional Riemannian manifolds. Finally, we present a simple but effective approximate BOT solver combining geometric optimization with a combinatorial optimization of the network topology.

Authors: Peter Lippmann, Enrique Fita Sanmartín, Fred A. Hamprecht

Date Published: 2022

Publication Type: Journal

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Authors: Regine Nessel, Thorsten Löffler, Johannes Rinn, Philipp Lösel, Samuel Voss, Vincent Heuveline, Matthias Vollmer, Johannes Görich, Yannique-Maximilian Ludwig, Luai Al-Hileh, Friedrich Kallinowski

Date Published: 15th Dec 2021

Publication Type: Journal

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Authors: S. Kashif Sadiq, Abraham Muñiz Chicharro, Patrick Friedrich, Rebecca C. Wade

Date Published: 14th Dec 2021

Publication Type: Journal

Abstract (Expand)

EnzymeML is an XML-based data exchange format that supports the comprehensive documentation of enzymatic data by describing reaction conditions, time courses of substrate and product concentrations, the kinetic model, and the estimated kinetic constants. EnzymeML is based on the Systems Biology Markup Language, which was extended by implementing the STRENDA Guidelines. An EnzymeML document serves as a container to transfer data between experimental platforms, modeling tools, and databases. EnzymeML supports the scientific community by introducing a standardized data exchange format to make enzymatic data findable, accessible, interoperable, and reusable according to the FAIR data principles. An application programming interface in Python supports the integration of software tools for data acquisition, data analysis, and publication. The feasibility of a seamless data flow using EnzymeML is demonstrated by creating an EnzymeML document from a structured spreadsheet or from a STRENDA DB database entry, by kinetic modeling using the modeling platform COPASI, and by uploading to the enzymatic reaction kinetics database SABIO-RK.

Authors: J. Range, C. Halupczok, J. Lohmann, N. Swainston, C. Kettner, F. T. Bergmann, A. Weidemann, U. Wittig, S. Schnell, J. Pleiss

Date Published: 11th Dec 2021

Publication Type: Journal

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