Evidence map›Paper›PMID 36222201›Full record

ArticleDatabase : the journal of biological databases and curation2022

KinMod database: a tool for investigating metabolic regulation.

Kiandokht Haddadi, Rana Ahmed Barghout, Radhakrishnan Mahadevan

Abstract read
In one paragraph

Article in Database : the journal of biological databases and curation, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

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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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3 · Its place in the literature

Who cites it

2 citing papers in PubMed.

  1. Review
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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.

Kiandokht HaddadiLaboratory for Metabolic Systems Engineering, BioZone, Center for Applied Biosciences and Bioengineering, Department of Chemical Engineering & Applied Chemistry, University of Toronto, 200 College St, Toronto, ON M5T 3A1, Canada.
Rana Ahmed BarghoutLaboratory for Metabolic Systems Engineering, BioZone, Center for Applied Biosciences and Bioengineering, Department of Chemical Engineering & Applied Chemistry, University of Toronto, 200 College St, Toronto, ON M5T 3A1, Canada.ORCID 0000-0002-7019-8118
Radhakrishnan MahadevanLaboratory for Metabolic Systems Engineering, BioZone, Center for Applied Biosciences and Bioengineering, Department of Chemical Engineering & Applied Chemistry, University of Toronto, 200 College St, Toronto, ON M5T 3A1, Canada.ORCID 0000-0002-1270-9063

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The ability of current kinetic models to simulate the phenotypic behaviour of cells is limited since cell metabolism is regulated at different levels including enzyme regulation. The small molecule regulation network (SMRN) enables cells to respond rapidly to environmental fluctuations by controlling the activity of enzymes in metabolic pathways. However, SMRN is not as well studied relative to metabolic networks. The main contributor to the lack of knowledge on this regulatory system is the sparsity of experimental data and the absence of a standard framework for representing available information. In this paper, we introduce the KinMod database that encompasses more than 2 million data points on the metabolism and metabolic regulation network of 9814 organisms KinMod database employs a hierarchical data structure to: (i) signify relationships between kinetic information obtained through in-vitro experiments and proteins, with an emphasis on SMRN, (ii) provide a thorough insight into available kinetic parameters and missing experimental measurements of this regulatory network and (iii) facilitate machine learning approaches for parameter estimation and accurate kinetic model construction by providing a homogeneous list of linked omics data. The hierarchical ontology of the KinMod database allows flexible exploration of data attributes and investigation of metabolic relationships within- and cross-species. Identifying missing experimental values suggests additional experiments required for kinetic parameter estimation. Linking multi-omics data and providing data on SMRN encourages the development of novel machine learning techniques for predicting missing kinetic parameters and promotes accurate kinetic model construction of cells metabolism by providing a comprehensive list of available kinetic measurements. To illustrate the value of KinMod data, we develop six analyses to visualize associations between data classes belonging to separate sections of the metabolism. Through these analyses, we demonstrate that the KinMod database provides a unique framework for biologists and engineers to retrieve, evaluate and compare the functional metabolism of species, including the regulatory network, and discover the extent of available and missing experimental values of the metabolic regulation. Database URL: https://lmse.utoronto.ca/kinmod/KINMOD.sql.gz.

Indexed as

Biochemical PhenomenaModels, BiologicalKineticsMachine LearningMetabolic Networks and Pathways

Identifiers

PMID36222201
PMCPMC9554645

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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.