Description
Title: NEXT-GENERATION SEQUENCED DATA HYBRID GENETIC DISEASE DIAGNOSTICS WITH SEMANTIC CAPABILITY
Abstract: Genome sequencing technology called “next generation sequencing” is used in genetics to diagnose disease. Finding the one mutation in a genome that causes a disease is difficult even with the list of mutations that NGS provides. Numerous applications for variant prioritization have been created, but the information they offer is more like a suggestion than a diagnosis, and they also suffer from problems like misclassifying a nonpathogenic variant as a causal one or failing to pinpoint the causal gene. These problems prompted us to develop a variant prioritization strategy that makes use of the Exomiser and OMIM Explorer result sets that have been enhanced by semantic analysis of free-to-access abstracts and articles from the PubMed and PubMed Central databases. The Google Scholar repository will be used to search for scientific articles with a broader scope. We can present the most up-to-date and accurate knowledge about potential pathogenic variants thanks to the described methodology.
Keywords: gene prioritization, variant prioritization, semantical text analysis
Paper Quality: SCOPUS / Web of Science Level Research Paper
Paper type: Analysis Based Research Paper
Subject: Computer Science
Writer Experience: 20+ Years
Plagiarism Report: Turnitin Plagiarism Report will be less than 10%
Restriction: Only one author may purchase a single paper. The paper will then indicate that it is out of stock.
What will I get after the purchase?
A turnitin plagiarism report of less than 10% in a pdf file and a full research paper in a word document.
In case you have any questions related to this research paper, please feel free to call/ WhatsApp on +919726999915
Reviews
There are no reviews yet.