FungiNet total (Julius Maximilians University Würzburg, Biocenter, Department of Bioinformatics) ; B1 (Friedrich Schiller University Jena, Department of Bioinformatics, School for Biology and Pharmacy)
Modelling interactions between the host and fungal pathogens by combining metabolic pathway analysis and evolutionary game theory
Interaction networks of signalling molecules and pathways between the pathogenic fungi Aspergillus fumigatus and Candida albicans and their human host
Dynamic optimization model to study control points in metabolic pathways to identify general strategies behind pathway regulation.
Toxic intermediates determine which enzyme control pathway flux and prevent their accumulation.
Therefore those enzymes are drug targets since deregulation leads to self-poisoning of pathogens.
Creator: Jan Ewald
Contributor: Jan Ewald
Model type: Ordinary differential equations (ODE)
Model format: Matlab package
Environment: Not specified
Organism: Not specified
Investigations: No Investigations
Studies: No Studies
Modelling analyses: No Modelling analyses
Date Published: 3rd Nov 2020
Journal: Open Biol
PubMed ID: 33142084
Citation: Open Biol. 2020 Nov;10(11):200206. doi: 10.1098/rsob.200206. Epub 2020 Nov 4.
Date Published: 30th Nov 2019
Journal: Cell Mol Life Sci
PubMed ID: 31776589
Citation: Cell Mol Life Sci. 2020 Feb;77(3):467-480. doi: 10.1007/s00018-019-03382-0. Epub 2019 Nov 27.
Date Published: 14th Jun 2019
Journal: Front Cell Infect Microbiol
PubMed ID: 31192161
Citation: Front Cell Infect Microbiol. 2019 May 22;9:168. doi: 10.3389/fcimb.2019.00168. eCollection 2019.
Date Published: 20th Feb 2019
Journal: PLoS One
PubMed ID: 30779817
Citation: PLoS One. 2019 Feb 19;14(2):e0212187. doi: 10.1371/journal.pone.0212187. eCollection 2019.
Date Published: 4th May 2018
Journal: J R Soc Interface
PubMed ID: 29720453
Citation: J R Soc Interface. 2018 May;15(142). pii: rsif.2017.0963. doi: 10.1098/rsif.2017.0963.