Журнал прикладной биоинформатики и вычислительной биологии

IMMUNE DB: A Large Internet Framework for Collecting and Analysing Biological Immune Results

Venu Paritala*, Rajashekhar Reddy S, Sukesh K and Bhargavi Pasupuleti

ata discovery is becoming increasingly dependent on bioinformatics analytic techniques and access to curated data repositories related to immune responses and particular pathogens. With the exponential growth of biological evidence, a growing number of biological databases have been created to assist humanimmune system-related research. We present a list of humanimmune system- related biological datasets and provided a minireview by categorizing them into various data forms. This paper is largely aimed at computer scientists with only a rudimentary understanding of biology Databases are replacing science literature as a means of disseminating this knowledge to the public immune disease database (https://venuparitala.shinyapps.io/immune_db/) apprehend the data cramped in figures, text, tables of the scientific literature promise it freely available and easily searchable to the public. Immune DB will assist biological researchers to explore about immune system categorized innate, autoimmune, and adaptive immune systems, each category has multiple disorders, each disorder has its own control and gene catalogue in summation with targets and networks. It discusses how to enhance immunity and which foods and medicines women and children can take. We covered which age individuals are suffering more, then after the information is provided about covid19 effects, symptoms, control, genes take place and collection of literature. It reflects the number of people of a certain age who have immune deficiency, as well as the percentage of people who can avoid and tolerate it. , this index includes all facets of 14 auto immune disorders, 1 adaptive immune disease, and 6 innate immune diseases, this database, which is accessible, compact, and open-source, should be useful to all.