PHI-Nets: A Network Resource for Ascomycete Fungal Pathogens to Annotate and Identify Putative Virulence Interacting Proteins and siRNA Targets.
PHI-base
biological networks
gene function inference
interactome inference
pathogenic fungi
small interfering RNA
Journal
Frontiers in microbiology
ISSN: 1664-302X
Titre abrégé: Front Microbiol
Pays: Switzerland
ID NLM: 101548977
Informations de publication
Date de publication:
2019
2019
Historique:
received:
01
09
2019
accepted:
08
11
2019
entrez:
24
12
2019
pubmed:
24
12
2019
medline:
24
12
2019
Statut:
epublish
Résumé
Interactions between proteins underlie all aspects of complex biological mechanisms. Therefore, methodologies based on complex network analyses can facilitate identification of promising candidate genes involved in phenotypes of interest and put this information into appropriate contexts. To facilitate discovery and gain additional insights into globally important pathogenic fungi, we have reconstructed computationally inferred interactomes using an interolog and domain-based approach for 15 diverse Ascomycete fungal species, across nine orders, specifically
Identifiants
pubmed: 31866958
doi: 10.3389/fmicb.2019.02721
pmc: PMC6908471
doi:
Types de publication
Journal Article
Langues
eng
Pagination
2721Subventions
Organisme : Biotechnology and Biological Sciences Research Council
ID : BB/I000488/1
Pays : United Kingdom
Informations de copyright
Copyright © 2019 Janowska-Sejda, Lysenko, Urban, Rawlings, Tsoka and Hammond-Kosack.
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