Evidence map›Paper›PMID 29353313›Full record

ArticleJournal of mathematical biology2018

General solution of the chemical master equation and modality of marginal distributions for hierarchic first-order reaction networks.

Matthias Reis, Justus A Kromer, Edda Klipp

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Article in Journal of mathematical biology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

3 citing papers in PubMed.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors.

Matthias ReisInstitute of Biology, Theoretical Biophysics, Humboldt-Universität zu Berlin, 10117, Berlin, Germany.
Justus A KromerCenter for Advancing Electronics Dresden, Technische Universität Dresden, 01062, Dresden, Germany.
Edda KlippInstitute of Biology, Theoretical Biophysics, Humboldt-Universität zu Berlin, 10117, Berlin, Germany. edda.klipp@hu-berlin.de.ORCID 0000-0002-0567-7075

Funding

Leibniz-Gemeinschaft 02208701
6 · The paper itself

Abstract

Multimodality is a phenomenon which complicates the analysis of statistical data based exclusively on mean and variance. Here, we present criteria for multimodality in hierarchic first-order reaction networks, consisting of catalytic and splitting reactions. Those networks are characterized by independent and dependent subnetworks. First, we prove the general solvability of the Chemical Master Equation (CME) for this type of reaction network and thereby extend the class of solvable CME's. Our general solution is analytical in the sense that it allows for a detailed analysis of its statistical properties. Given Poisson/deterministic initial conditions, we then prove the independent species to be Poisson/binomially distributed, while the dependent species exhibit generalized Poisson/Khatri Type B distributions. Generalized Poisson/Khatri Type B distributions are multimodal for an appropriate choice of parameters. We illustrate our criteria for multimodality by several basic models, as well as the well-known two-stage transcription-translation network and Bateman's model from nuclear physics. For both examples, multimodality was previously not reported.

Indexed as

Models, BiologicalBiocatalysisBiochemical PhenomenaComputer SimulationKineticsLinear ModelsMathematical ConceptsMetabolic Networks and PathwaysModels, ChemicalPoisson DistributionProbabilityProtein BiosynthesisTranscription, GeneticBursting processChemical master equationCompound processConditional multimodalityGeneralized binomial distributionGeneralized poisson distributionHierarchically linear ODE systemHierarchic reaction networkNuclear decay chainTranscription–translation model

Identifiers

PMID29353313
PMCPMC6061068

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.