MIT EECS - Wertheimer Undergraduate Research and Innovation Scholar
Cell-cycle state classifier from gene expression data
David K. Gifford
Cell reproduction is an important field of research because it’s a process where abnormal function can lead to serious problems. The genes expressed by a cell control the RNA and proteins produced, and therefore everything that happens in the cell, including the cell-cycle phase (where in the process of division the cell is). The goal of this project is to create and evaluate a model, using machine learning techniques, which can predict cell-cycle phase based on gene expression data. Such a model would give researchers more information from RNA sequencing data, and the process of developing it will bring to light genes with strong predictive power, which are likely to have a biological role in cell division.
I have a strong understanding of machine learning methods from 6.036 and an interest in applying computer science to biological research, as I did in my summer research analyzing the motions of microswimmers. I also have experience with large data sets from working as an intern at Akamai Technologies and as an UROP in the computational linguistics department.