eternal-flame-ad/projects-utdallas — explained in plain English
Analysis updated 2026-07-19 · repo last pushed 2024-05-01
Browse a graduate student's computational biology projects to evaluate their data science skills.
Review a leukemia survival prediction project that uses genetic data and predictive modeling.
Look at a journal club presentation on CRISPR-based gene regulation techniques.
Use as a template for organizing your own academic portfolio with HTML.
| eternal-flame-ad/projects-utdallas | 100/rutgers-pbl-dining-2015 | a15n/a15n_old | |
|---|---|---|---|
| Language | HTML | HTML | HTML |
| Last pushed | 2024-05-01 | 2015-12-01 | 2016-06-18 |
| Maintenance | Dormant | Dormant | Dormant |
| Setup difficulty | easy | easy | easy |
| Complexity | 1/5 | 1/5 | 1/5 |
| Audience | researcher | general | general |
Figures from each repo's GitHub metadata at analysis time.
Static HTML files that can be viewed directly in a browser with no setup or dependencies required.
This repository is a personal collection of academic coursework completed by a student earning a Master's degree in Computational Biology at UT Dallas. It serves as a centralized portfolio, organizing various projects and presentations from different classes into one easy-to-browse location. Anyone looking to see what a computational biology graduate student actually works on can explore this collection. Inside, you will find a couple of specific examples of graduate-level work. One project focuses on predicting the survival chances of patients with a type of leukemia using their genetic data and a predictive modeling technique. Another entry is a journal club presentation about a method for editing how genes are turned on or off, based on the CRISPR technology you might have heard about in the news. The README does not go into detail about other coursework, so these two items are the only featured examples. Recruiters, hiring managers, or academic advisors are the most likely audience for this collection. It provides concrete proof of the student's ability to work at the intersection of biology and data science. Instead of just claiming to know how to analyze genetic data or understand complex biological research, the student can point people here to see the actual work. It is essentially a specialized, technical resume. The entire collection is shared under a Creative Commons license, which allows others to share and adapt the work as long as they give appropriate credit and distribute their new creations under the same terms. This makes sense for an academic portfolio, as course projects often build upon existing research and resources that carry their own sharing requirements.
A portfolio of academic coursework from a UT Dallas computational biology master's student, featuring projects like leukemia survival prediction and a CRISPR gene-editing journal club presentation.
Mainly HTML. The stack also includes HTML, Computational Biology, Predictive Modeling.
Dormant — no commits in 2+ years (last push 2024-05-01).
You can share and adapt this work as long as you give appropriate credit and distribute your new creations under the same license terms.
Setup difficulty is rated easy, with roughly 5min to a first successful run.
Mainly researcher.
This repo across BitVibe Labs
Verify against the repo before relying on details.