Investigating Differential Gene Expression in Cancer
Cancer is a tough disease to counter. Several cancers are caused to mutations in key oncogenes which lead to altered cell signaling resulting in changes in the transcriptome and proteome. These changes serve to drive altered metabolism in cancer cell to sustain proliferation despite nutrient deplete and harsh tumor micro-environments. The goal of this mini-project is mine clinical tumor RNA-seq data from publicly available repositories, identify suitable controls and investigate differential gene expression as a response to specific oncogenic drivers such as K-ras, c-Myc etc. One of the challenges is to identify biomarkers specific to the oncogenic drivers, as mutations tend to stack up and there are potential interaction effects.
The candidate will aim to mine a large dataset to perform differential expression analysis. The data would likely reveal trends and possible relations between oncogenic mutations and resulting gene expression. Eventually, the candidate understand experiment design and relevant bioinformatics tools which could prove helpful if an advanced degree is sought in this field.
Basic knowledge related to Python and R, Design of experiments, Statistics
Project Duration (in Months)
Number of openings
The mentor is an experimentalist and has some experience in bioinformatics and will guide the candidate on acquiring the right skills and domain knowledge. However, the candidate must independently work to develop the code required.
Knowledge in basic biology and biochemistry is preferred, although not necessary as it can be learnt as we go through the project.