pyodesys: Straightforward numerical integration of ODE systems from Python

Dahlgren, Björn

doi:10.21105/joss.00490

Cited by 9 publications

(6 citation statements)

References 3 publications

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“…We used to create systems of ODEs from chemical equations and to integrate the systems of ODEs numerically with . , Although numerical integration comes at the cost of slower posterior evaluations during inference, we believe that in many scenarios deploying models rapidly, as facilitated by the described set of tools, is more important than reduced computational cost, especially if there are numerous hypotheses to test.…”

Section: Methodsmentioning

confidence: 99%

Bayesian Data Integration Questions Classic Study on Protease Self-Digest Kinetics

Tötsch

Hoffmann

2020

ACS Omega

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We combine Bayesian data integration with kinetic modeling to rigorously identify reaction mechanisms. This approach forces models to be consistent not only with kinetic measurements but with all available information. We revisit a classic study on trypsin self-digest acceleration by colloidal silica. Bayesian data integration reveals that the mechanism suggested in that study is inconsistent with its presented data. We propose an improved hypothesis. However, the detailed mechanism of the surface reaction cannot be inferred from the available data.

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Section: Methodsmentioning

confidence: 99%

Bayesian Data Integration Questions Classic Study on Protease Self-Digest Kinetics

Tötsch

Hoffmann

2020

ACS Omega

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“…The temperature dependence of the rate constants was assumed to follow the Eyring equation in the investigated temperature interval (Figure S2). The following set of ordinary differential equations was then solved numerically, using an open source software package pyodesys, in parallel to determine the rates of changes in the concentration of free ligand ( L ) as well as the concentrations of liganded (NL), unliganded ( N ), unfolded ( U ), and aggregated ( A ) forms of the target protein: …”

Section: Methodsmentioning

confidence: 99%

Quantitative Interpretation of Intracellular Drug Binding and Kinetics Using the Cellular Thermal Shift Assay

et al. 2018

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Evidence of physical interaction with the target protein is essential in the development of chemical probes and drugs. The cellular thermal shift assay (CETSA) allows evaluation of drug binding in live cells but lacks a framework to support quantitative interpretations and comparisons with functional data. We outline an experimental platform for such analysis using human kinase p38α. Systematic variations to the assay’s characteristic heat challenge demonstrate an apparent loss of compound potency with an increase in duration or temperature, in line with expectations from the literature for thermal shift assays. Importantly, data for five structurally diverse inhibitors can be quantitatively explained using a simple model of linked equilibria and published binding parameters. The platform further distinguishes between ligand mechanisms and allows for quantitative comparisons of drug binding affinities and kinetics in live cells and lysates. We believe this work has broad implications in the appropriate use of the CETSA for target and compound validation.

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“…The library's algorithms are implemented using NumPy (Walt, Colbert, & Varoquaux, 2011), SciPy (Jones, Oliphant, Peterson, & others, 2001), matplotlib (Hunter, 2007), SymPy (Meurer et al, 2017), Cython (Behnel et al, 2011), pycvodes (Dahlgren, 2018) and fastcache (Brady, 2014). The library provides an application programming interface (API) for simulating planar skiing along arbitrary surface cross sections and two dimensional flight trajectories.…”

Section: Figure 1: Screenshot Of the Online Application Depicting Thementioning

confidence: 99%

skijumpdesign: A Ski Jump Design Tool for Specified Equivalent Fall Height

Moore¹,

Hubbard²

2018

JOSS

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pyodesys: Straightforward numerical integration of ODE systems from Python

Cited by 9 publications

References 3 publications

Bayesian Data Integration Questions Classic Study on Protease Self-Digest Kinetics

Bayesian Data Integration Questions Classic Study on Protease Self-Digest Kinetics

Quantitative Interpretation of Intracellular Drug Binding and Kinetics Using the Cellular Thermal Shift Assay

skijumpdesign: A Ski Jump Design Tool for Specified Equivalent Fall Height

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