Submitted by Steven E. Brenner on
Gene expression in eukaryotes is regulated at several stages including initialization of mRNA transcription, post-translational modification, and nonsense-mediated mRNA decay (NMD). NMD is found to affect hundreds to thousands of human genes and its regulatory role in human tissues is largely unexplored.
We are now uncovering a high-confidence set of NMD targets by studying the transcriptome with key NMD splicing factors knocked down. The goal of this project is to develop a computational method to estimate the overall efficiency of NMD based on this confident set of NMD targets, apply it to human transcriptomes (both normal tissues and diseases), and develop a web tool.
Thus, the project will involve analyses of RNA-seq data, basic programming with perl/python, R language, and web development. After enrolling, the applicant will be trained in bioinformatics skills.
You will work closely with Brenner Lab postdoctoral researcher Zhiqiang Hu to develop a computational method to estimate the overall efficiency of NMD based on this confident set of NMD targets, apply it to human transcriptomes (both normal tissues and diseases), and develop a web tool. The project will involve analyses of RNA-seq data, basic programming with perl/python, R language, and web development. After enrolling, you will be trained in bioinformatics skills.
The student should have a keen interest in bioinformatics and should be familiar with at least one programming language. Applicants with a GPA less than 3.6 will be considered only in exceptional circumstances. The student must be able to attend 3-hour lab meeting every week, attend a subgroup meeting every week, adhere to other lab policy (including weekly notebooks to track research, semester reports) and register for credits, regardless of their program-specific requirements. Our lab is interdisciplinary, and we want to get a holistic picture of your background, so please include your unofficial transcript with your application.