Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Articles Article Faculty Publications -Articles Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource An Investigation of Complex Interactions Between Genetically Determined Protein Expression and the Metabolic Phenotype of Human Islet Cells Using Deep Learning Subject The topic of the resource BiLSTM; BLB; Deep learning; EfficientNet B0; eQTL; PIMA; Type 2 diabetes Description An account of the resource The relationship between gene modules and several genome-scale metrics was examined, including heterozygosity that caused type 2 diabetes due to insulin deuteration, differential expression, genotyping association, methylation, and copy number changes. This work investigates the complex relationships between protein expression, genetic polymorphisms, and metabolic properties of human islet cells using expression quantitative trait loci (eQTL) detection. We looked at the genomic, transcriptomic, and proteomic information from islet cells in persons with type 2 diabetes. From the information from different levels, we noticed novel eQTLs that regulate crucial metabolic and signaling pathways in islet cells. Our study highlights the importance of a systems-level approach in understanding the complicated biological processes by highlighting the complexity of the link between genetic variants, protein expression, and metabolic abnormalities using the PIMA Indian dataset. Our findings provide novel insights into the molecular mechanisms behind islet cell failure in type 2 diabetes, potential targets for emerging treatment strategies, and the genomic implications of variations in gene expression, mutations, and other factors. To accomplish this purpose, we proposed a novel BLB model and obtained 99.89%. 2023, The Author(s), under exclusive licence to Springer Nature Singapore Pte Ltd. Creator An entity primarily responsible for making the resource Padmaja K.; Mukhopadhyay D. Source A related resource from which the described resource is derived SN Computer Science, Vol-4, No. 6 Publisher An entity responsible for making the resource available Springer Date A point or period of time associated with an event in the lifecycle of the resource 2023-01-01 Identifier An unambiguous reference to the resource within a given context <a href="https://doi.org/10.1007/s42979-023-02222-0" target="_blank" rel="noreferrer noopener">https://doi.org/10.1007/s42979-023-02222-0</a> <br /><br /><a href="https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173924022&amp;doi=10.1007%2Fs42979-023-02222-0&amp;partnerID=40&amp;md5=0a303c30e06e88dac7a2e27819f0872b" target="_blank" rel="noreferrer noopener">https://www.scopus.com/inward/record.uri?eid=2-s2.0-85173924022&amp;doi=10.1007%2fs42979-023-02222-0&amp;partnerID=40&amp;md5=0a303c30e06e88dac7a2e27819f0872b</a> Rights Information about rights held in and over the resource Restricted Access Relation A related resource ISSN: 2662995X Format The file format, physical medium, or dimensions of the resource Online Language A language of the resource English Type The nature or genre of the resource Article Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Padmaja K., Department of CSE, CHRIST (Deemed to be University), Karnataka, Bangalore, India; Mukhopadhyay D., Department of CSE, CHRIST (Deemed to be University), Karnataka, Bangalore, India