Open AccessGeneArticleAnalyser: A crucial part of the genome and word data analysis identification from Pub Med articles
Publication year - 2022
Publication title -
international journal of emerging trends in engineering research
Language(s) - English
Resource type - Journals
ISSN - 2347-3983
DOI - 10.30534/ijeter/2022/031032022
Subject(s) - identification (biology) , computer science , process (computing) , quality (philosophy) , data science , word (group theory) , genome , world wide web , gene , biology , genetics , linguistics , philosophy , botany , epistemology , operating system
A crucial parting of genome data analysis is identification from articles. Despite the availability of several articles in NCBI, researchers need to list out the genes, words, and quality of the genes from different articles, this process is highly timeconsuming and requires a high throughput computing knowledge with advanced infrastructure. Hence, a user-friendly, single portal that could solve these shortcomings is a high prerequisite for genes & words analysis. Herein we introduce our indigenously developed web application, gene-article analyzer, for the effective analysis of abstract text file format/PubMed file format. It encompasses several innovative features to perform genes, gene quality analysis, top genes, words, word quality analysis, top words, and network of literature evidence. To our knowledge, the gene-article analyzer is the first of its kind to perform all these analyses in a single click. Gene-article analyzer proves to be a powerful tool for data analysis pipelines that are applied from various applications like big data analysis. Innovation in recent years has promoted marked progress in understanding genes. This review presents the analysis of biological data, scrutinizing approaches, and tools that tin give biological meaning to the data produced.