Background
The Osborne Nishimura lab is offering a hands-on research opportunity to work with Dr. David C. King on a project that involves computer work, including analysis, related to biosciences. This position offers mentorship on projects of any skill level, from basic coding to analysis-based research. See below for potential topics.
Requirements
- Must be an undergraduate at Colorado State University or a community college.
- Interest in learning computational skills.
- Interest in biology.
- The project will be geared toward your skill level, but basic computer literacy (preference for some coding experience) is a must.
- Second year or higher.
Preferred Majors
- Computer Science
- Data science
- Biochemistry/Biology/BMS
Compensation
$15/hour is available for a summer term. Maximum 20 hours per week. Compensate with credits instead, if desired. Start date mid July.
Project and Research Goal
The project will be built around the biological question “what transcription factors work with ELT-2 in the C. elegans intestine?” ELT-2 is a developmental transcription factor that plays a large role in defining the intestine, and driving the expression of genes throughout the lifespan of of the worm. However, our work indicates that the real gene regulatory network is more complex, indicating the additional influence of unknown factors.
The preferred student will contribute to approaches that address this question using bioinformatics according to their technical background, and focusing on specific desired skills they wish to attain.
The student will choose one of the following projects:
No coding experience required
1) Basic coding project
Use R/Python/Command Line to help implement pipelines. Work together on basic coding tutorials, such as Swirl (for R), Rosalyn (for python) and/or BASH for shell and command line learning.
If you are interested java, c++, javascript, php, or SQL, there are applications for those too that we can discuss.
2) Web-based projects
Although scripting and coding is often needed, a lot of computational biology takes advantage of web-based analysis servers. We will learn to navigate data, submit it for analysis, and organize and present the results.
Examples include motif-finding and other statistical methods.
Familiarity with R required
3) Machine learning project
Required: basic coding in R. We will use R to explore approaches that evaluate supervised learning models that predict gene responses to transcription factor mutations or other experimental perturbations.
4) Interactive data visualization project
Required: basic coding in R. Interactive data visualization makes exploration much more accessible than static imagery, especially for large data. Based on R, we will use interactive applications to provide searching, alternate viewing options and other capabilities to genomic data exploration related to the project goals.
To apply
To apply, submit the following form with your name, email, and some info about your interests and goals.