Variant Impact Predictor Database (VIPdb)
Steven Brenner, Professor
Plant and Microbial Biology
Closed. This professor is continuing with Spring 2024 apprentices on this project; no new apprentices needed for Fall 2024.
Genome sequencing identifies a vast number of genetic variants. Predicting these variants’ molecular and clinical effects is one of the preeminent challenges in genetics. Accurate prediction of the impact of genetic variants improves our understanding of how genetic information yields molecular and cellular functions and is an essential step toward precision medicine. Over one hundred tools/resources have been developed specifically for this purpose. We have summarized these tools based on their characteristics in the genetic Variant Impact Predictor Database (VIPdb) (Hu et al., 2019). This database has helped researchers and clinicians explore appropriate tools and inform the development of improved methods.
In this project, we want to update the VIPdb to incorporate the new tools, developed in the past few years. The student will learn about methods and their features. This project will then include three parts: (1) Systematically searching for and identifying variant impact predictor tools based on literature databases, references, and other resources. (2) Collecting and summarizing the characteristics of the tools. (3) Updating the VIPdb website and publishing a paper.
VIPdb paper: Hu Z, Yu C, Furutsuki M, Andreoletti G, Ly M, Hoskins R, Adhikari AN, Brenner SE. 2019. VIPdb, a genetic variant impact predictor database. Hum Mutat. doi:10.1002/humu.23858
Qualifications: (1) Willing to learn and conduct research in a fast-paced environment.
(2) Knowledge of next-generation sequencing (NGS) data analysis or programming languages (R or Python) is a plus.
(3) Candidates must:
• Attend a 3-hour lab meeting every week.
• Attend a research subgroup meeting every week.
• Adhere to all lab policies (including weekly notebooks to track research and semester reports).
• Must register for credits, regardless of program-specific requirements.
(4) The student is required to continue the project during the Spring 2023 semester and full time in Summer 2023, if the student is invited to do so by the lab.
(5) Applicants with GPA under 3.6 will be considered only in exceptional circumstances.
Day-to-day supervisor for this project: Yu-Jen (Jennifer) Lin, Graduate Student
Hours: 12 or more hours
Related website: http://compbio.berkeley.edu
Related website: http://compbio.berkeley.edu