Abstract
Healthcare is a major area of research since few years. Ample amount of biological data getting accumulated daily due to advancement in technologies. Microarray is such technology which captures expressions of thousands of genes at a time. Interactions occur among genes are represented in terms of special networkeknown as Gene Regulatory Network (GRN). It is constructed from Differentially Expressing Genes(DEFs). GRN is a graphical representation containing genes as nodes and regulatory interactions among them as edges. It helps in tracking pathways where usual gene interaction changes leading to malfunctioning of cells and results in illness. Also, now a day’s people are diagnosed with new diseases like dengue, swine flu, Nipah, Corona virus infection for which exact molecular pathways are yet to be invented through GRN. Therefore, in this paper, a nature inspired algorithm is used for reconstruction of GRN using differentially expressing genes.
Highlights
Genes contain blue print of living organisms
Advanced technology like microarray plays an important role in gene expression analysis as it captures expressions of ethousands of genes under different conditions esimultaneously
Those genes which behave differently under stress conditions are called as Differentially Expressing Genese (DEGs)
Summary
Genes contain blue print of living organisms. All cell activities are controlled by synthesis of proteins whose disproportionate share causes malfunctioning in cellular activity. Some gene products known as proteins are required by cells under all growth conditions. Some gene products are required under specific growth conditionse These include enzymes that synthesize amino acids, break down specific sugars, or respond to a specific environmental condition such as DNA damagee [1]. Advanced technology like microarray plays an important role in gene expression analysis as it captures expressions of ethousands of genes under different conditions esimultaneously. Those genes which behave differently under stress conditions are called as Differentially Expressing Genese (DEGs). Identifying gene interactions is a major challenge in post genomic era It helps in knowing how cells maintain their form. Though vast amount of biological data getting accumulated day by day, a technique is needed which will successfully model uncertainty lies in gene expressions in terms of GRN
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