Computational Study of Long Noncoding RNAs in Cancer
Project Description

Cancer is still an incurable disease, caused by the accumulation of somatic mutations. The recent technologies in high-throughput experimentation and next-generation sequencing have generated a huge amount of data, providing a unique opportunity to computationally challenge this deadly disease. This project will focus on the study of long noncoding RNAs in cancer. Particularly, we will use glioblastoma, an aggressive type of brain tumor as a proof-of-concept example to identify noncoding RNAs that might play important role in cancer progression.

Supervisor
WANG Jiguang
Quota
2
Course type
UROP1000
UROP1100
UROP2100
UROP3100
UROP4100
Applicant's Roles

The applicants will develop software to identify noncoding RNAs from RNA-sequencing data.

Requirements: good programming skills, good mathematical background, and basic biology knowledge

Applicant's Learning Objectives

Objective 1: to be able to analyze RNA-sequencing data with shell scripts;

Objective 2: to be able to perform statistical analyses to identify significant noncoding RNAs and illustrate the results;

Objective 3: to finish a project report by summarizing the studies.

Complexity of the project
Challenging