Novel Deleterious nsSNPs within MEFV Gene that Could Be Used as Diagnostic Markers to Predict Hereditary Familial Mediterranean Fever: Using Bioinformatics Analysis
Clicks: 761
ID: 7721
2019
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.
Reader Engagement
Emerging Content
71.7
/100
761 views
566 readers
Trending
AI Quality Assessment
Not analyzed
Readership in this journal
EmergingRanked #1 of 78 articles by views in advances in bioinformatics
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate 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
Background. Familial Mediterranean Fever (FMF) is the most common autoinflammatory disease (AID) affecting mainly the ethnic groups originating from Mediterranean basin. We aimed to identify the pathogenic SNPs in MEFV by computational analysis software. Methods. We carried out in silico prediction of structural effect of each SNP using different bioinformatics tools to predict substitution influence on protein structure and function. Result. 23 novel mutations out of 857 nsSNPs are found to have deleterious effect on the MEFV structure and function. Conclusion. This is the first in silico analysis of MEFV gene to prioritize SNPs for further genetic mapping studies. After using multiple bioinformatics tools to compare and rely on the results predicted, we found 23 novel mutations that may cause FMF disease and it could be used as diagnostic markers for Mediterranean basin populations.
| Reference Key |
i2019noveladvances
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | Mustafa, Mujahed I.;Abdelhameed, Tebyan A.;Abdelrhman, Fatima A.;Osman, Soada A.;Hassan, Mohamed A.;Mustafa, Mujahed I.;Abdelhameed, Tebyan A.;Abdelrhman, Fatima A.;Osman, Soada A.;Hassan, Mohamed A.; |
| Journal | advances in bioinformatics |
| Year | 2019 |
| DOI |
10.1155/2019/1651587
|
| URL | |
| 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.