Type II Diabetes RNA atlas

Active:

true

Description

Diabetes is a chronic metabolic syndrome characterized by a very high blood glucose level. There are two types of diabetes, types 1 and 2, where type 2 diabetes (T2D) is more common. The current treatment options for T2D include changes in diet, weight loss, and drugs (e.g., metformin) to lower blood glucose level. Because of the increasing cases of T2D around the world, the research to find the disease mechanism and possible cure has intensified in recent years. These research efforts have produced a number of RNA sequencing (RNA-seq) data. Yet, most of these data are only analyzed for protein-coding genes, although the RNA-seq technique surveys any types of RNA, including those of non-protein-coding RNAs [e.g., long non-coding RNAs (lncRNAs)]. LncRNAs are considered as missing links to understand signaling pathways, including those affected by T2D. However, there is no expression database for lncRNAs in T2D patients compared to healthy donors. In this project, we will make a knowledge database for both protein-coding and lncRNA genes in T2D. The database architecture will be similar to our previous databases, FibroDB (https://rnamedicine.shinyapps.io/FibroDB/) and LiverDB (https://rnamedicine.shinyapps.io/LiverDB/).

R

RNA-Seq, Data mining, R-Shiny

Project Stage

Late

Avg. Hours / Week

6

Project Provider

Shizuka Uchida, PhD

Commitment (Months)

3

Spots Open

1

Project Lead

TBD

Publication if successful?

Yes

Trainee authorship criteria (if applicable)

The BRN trainees will be co-authors.

Required Skill Assessments

Basic Data Science Web Development

R Programming

Linux for Bioinformatics

RNA-Seq Analysis

R for Data Science