VFDB 2016: hierarchical and refined dataset for big data analysis—10 years on

Clicks: 3
ID: 292434
2015
Free PDF
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Emerging

Ranked #1,019 of 1,217 articles by views in Nucleic Acids Research

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 1,217 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
The virulence factor database (VFDB, http://www.mgc.ac.cn/VFs/) is dedicated to providing up-to-date knowledge of virulence factors (VFs) of various bacterial pathogens. Since its inception the VFDB has served as a comprehensive repository of bacterial VFs for over a decade. The exponential growth in the amount of biological data is challenging to the current database in regard to big data analysis. We recently improved two aspects of the infrastructural dataset of VFDB: (i) removed the redundancy introduced by previous releases and generated two hierarchical datasets – one core dataset of experimentally verified VFs only and another full dataset including all known and predicted VFs and (ii) refined the gene annotation of the core dataset with controlled vocabularies. Our efforts enhanced the data quality of the VFDB and promoted the usability of the database in the big data era for the bioinformatic mining of the explosively growing data regarding bacterial VFs.
Reference Key
openalex_W2173913502 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Lihong Chen, Dandan Zheng, Bo Liu, Jian Yang, Qi Jin
Journal Nucleic Acids Research
Year 2015
DOI
10.1093/nar/gkv1239
URL
https://academic.oup.com/nar/article-pdf/44/D1/D694/16661734/gkv1239.pdf
Keywords Keywords not found

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.