gene-disease interaction retrieval from multiple sources: a network based method

Clicks: 6
ID: 236036
2016
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
Steady

Ranked #1,301 of 1,324 articles by views in spectrochimica acta - part a: molecular and biomolecular spectroscopy

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 1,324 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
Abstract
The number of gene-related databases has been growing largely along with the research on genes of bioinformatics. Those databases are filled with various gene functions, pathways, interactions, and so forth, while much biomedical knowledge about human diseases is stored as text in all kinds of literatures. Researchers have developed many methods to extract structured biomedical knowledge. Some study and improve text mining algorithms to achieve efficiency in order to cover as many data sources as possible, while some build open source database to accept individual submissions in order to achieve accuracy. This paper combines both efforts and biomedical ontologies to build an interaction network of multiple biomedical ontologies, which guarantees its robustness as well as its wide coverage of biomedical publications. Upon the network, we accomplish an algorithm which discovers paths between concept pairs and shows potential relations.
Reference Key
huang2016biomedgene-disease Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Lan Huang;Ye Wang;Yan Wang;Tian Bai
Journal spectrochimica acta - part a: molecular and biomolecular spectroscopy
Year 2016
DOI
10.1155/2016/3594517
URL
Keywords

Citations

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

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