Neveen Mohamed
I am an experienced engineering professional, developer, and analyst currently pursuing an MS in Bioinformatics at Northeastern University in Boston, a natural progression that combines my foundational Master’s in Electrical Engineering with two years of rigorous premed coursework and a strong background in Data Science and Machine Learning. This unique blend of expertise in engineering, biology, and data science enables me to bring analytical thinking and innovation to every project. As a Kaggle contributor and Instructor, I stay informed of industry trends while continuously expanding my knowledge. Beyond my professional pursuits, I take pride in being a mother, and I find rejuvenation in yoga and hiking. I also have a deep passion for classical music, enjoying it whether I’m driving, working, or attending performances at the theater.
Before Northeastern I joined Kaggle and with Northeastern I’m enjoying my discussions and projects
Let me share some of my recent projects.
Analyzing The Discovered ORF among Contigs
20 contigs read from a file were parsed and the Motif scored. I used visualizations everywhere in my code from histograms to lines to pies to analyze the results: so cool!
DeepTE sbatch and python scripts
Transposable elements come from many models and DeepTE classifies them using a collection of CNN. In my project, I created many Python and bash scripts to utilize DeepTE and analyze its output!
Assembling Short Reads into Contigs
Assembling short reads into contigs depends on the overlap length. adopting an overlap of 10 bases and visualizing the results then changing the overlap length to lower or higher and noticing the difference. how does it affect the coverage?
XGBoost for Prakinson’s disease progression
This project was part of my entry into the Kaggle competition. I developed a model that predicts the progression of Parkinson’s disease using XGBoost with measured precision and accuracy scores above 90%
