Interest in the Planctomycetes-Verrucomicrobia-Chlamydiae (PVC) bacterial superphylum is growing within the microbiology community. These organisms do not have a specialized web resource that gathers in silico predictions in an integrated fashion. Hence, we are providing the PVC community with PVCbase, a specialized web resource that gathers in silico predictions in an integrated fashion. PVCbase integrates protein function annotations obtained through sequence analysis and tertiary structure prediction for 39 representative PVC proteomes (PVCdb), a protein feature visualizer (Foundation) and a custom BLAST webserver (PVCBlast) that allows to retrieve the annotation of a hit directly from the DataTables. We display results from various predictors, encompassing most functional aspects, allowing users to have a more comprehensive overview of protein identities. Additionally, we illustrate how the application of PVCdb can be used to address biological questions from raw data.

PVCbase: an integrated web resource for the PVC bacterial proteomes

Bordin, N
;
2018

Abstract

Interest in the Planctomycetes-Verrucomicrobia-Chlamydiae (PVC) bacterial superphylum is growing within the microbiology community. These organisms do not have a specialized web resource that gathers in silico predictions in an integrated fashion. Hence, we are providing the PVC community with PVCbase, a specialized web resource that gathers in silico predictions in an integrated fashion. PVCbase integrates protein function annotations obtained through sequence analysis and tertiary structure prediction for 39 representative PVC proteomes (PVCdb), a protein feature visualizer (Foundation) and a custom BLAST webserver (PVCBlast) that allows to retrieve the annotation of a hit directly from the DataTables. We display results from various predictors, encompassing most functional aspects, allowing users to have a more comprehensive overview of protein identities. Additionally, we illustrate how the application of PVCdb can be used to address biological questions from raw data.
2018
File in questo prodotto:
Non ci sono file associati a questo prodotto.
Pubblicazioni consigliate

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/3597620
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 14
  • ???jsp.display-item.citation.isi??? 13
  • OpenAlex ND
social impact