Prediction of Type2 Diabetes using Insulin DNA Sequence

This research paper addresses the challenge of objectively evaluating diverse biological characteristics through the classification of DNA sequences. Identifying DNA sequences in genomics research can aid in discovering novel protein activities, such as insulin, which regulates blood sugar levels in the human body. Diabetes, a prevalent chronic illness, is linked to changes in the insulin gene sequence. The study aims to develop a machine-learning model to categorize the insulin gene's DNA sequence and identify type 2 diabetes based on this transformation. The model's performance will be compared to existing machine-learning models. Additionally, the research seeks to identify unique gene variants of the insulin protein associated with diabetes prognosis and investigate the risk factors associated with these gene variants.

Authors

Institutions

Publication Details

Journal
Mapana Journal of Sciences
Published
2024-11-06
DOI
https://doi.org/10.12723/mjs.sp3.7
Primary Topic
Machine Learning in Bioinformatics
Type
article
Field-Weighted Citation Impact
0.00
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Prediction of Type2 Diabetes using Insulin DNA Sequence

Aswathi Sasidharan
Mapana Journal of Sciences
Machine Learning in Bioinformatics
article

Prediction of Type2 Diabetes using Insulin DNA Sequence

Aswathi Sasidharan
article en

Abstract

This research paper addresses the challenge of objectively evaluating diverse biological characteristics through the classification of DNA sequences. Identifying DNA sequences in genomics research can aid in discovering novel protein activities, such as insulin, which regulates blood sugar levels in the human body. Diabetes, a prevalent chronic illness, is linked to changes in the insulin gene sequence. The study aims to develop a machine-learning model to categorize the insulin gene's DNA sequence and identify type 2 diabetes based on this transformation. The model's performance will be compared to existing machine-learning models. Additionally, the research seeks to identify unique gene variants of the insulin protein associated with diabetes prognosis and investigate the risk factors associated with these gene variants.

Mapana Journal of SciencesVol. 23
Christ University (IN)
Openalex Percentile: Top 78%
Machine Learning in Bioinformatics
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.