Dr. Melyssa Bratton is a research scientist at Xavier University in New Orleans, Louisiana. Along with managing the cell, molecular and bioinformatics core laboratory at Xavier, Dr. Bratton also does independent research on breast cancer. She was part of the Louisiana Biomedical Research Network (LBRN) Summer 2019 Bioinformatics Training Program and Hackathon, a collaboration between Pine Biotech and LBRN.
The LBRN Bioinformatics Training Program was designed for faculty and students to learn and develop projects using public-domain NGS transcriptomics data. During the program, participants got hands-on training on topics like finding and evaluating Next Generation Sequencing data, quality control, processing, and differential analysis and interpretation.
For her research project, Dr. Bratton led a team with colleagues at Louisiana State University to study early detection of breast cancer. In the past, she studied the effects of fluid shear stress on both genomic and phenomic changes in breast cancer cells. She used next generation sequencing, in combination with PCR arrays and Western blotting, to interrogate molecular pathways affected by shear stress.
Dr. Bratton has gained bioinformatics experience taking bioinformatics courses on the edu.t-bio.info portal and participating in a number of OmicsLogic bioinformatics training programs to learn more about analysis of genomic and transcriptomics data. You can check out her edu profile here: https://edu.t-bio.info/members/melyssa-bratton/. As a result of her studies, she acquired over 5000 points and is 98th on our leaderboard.
This is what Dr. Bratton had to say about her experience:
“My group was in the Targeted Medicine study. I was the lead and since my interest is in breast cancer, we decided to use a machine learning approach to try to find biomarkers in patient blood samples (cell free DNA) to diagnose early stage breast cancer. We used published next generation RNA-sequencing data from two populations of tissue, normal breast and DCIS (ductal carcinoma in situ). While we only had a few months to work on this project, I learned a great deal about pipeline development and machine learning in general. I also got a good introduction to analyzing RNA-seq data sets. I followed this up with a short course on next generation sequencing called OmicsLogic, Genomic DNA analysis which reinforced what I had already learned in the previous summer course. I really like the plug and play pipeline that PineBio has developed and think it is a great teaching tool for undergraduate and graduate bioinformatics students.”