Iva Monique Tejero Gramatikov
MIT BE | Microbiome Undergraduate Research and Innovation Scholar
Machine Learning and In Silico Peptide Design
2017–2018
BE/UBIOME
- Artificial Intelligence for Healthcare and Life Sciences
Timothy K. Lu
Cesar de La Fuente Nunez
A grand challenge in medicine today is the inability to rationally manipulate the human microbiome. Despite its established importance in both health and disease, we currently lack tools to precisely engineer these microbial communities. Recently, we have generated synthetic peptides that can be used to manipulate the human microbiome. We have synthesized and performed functional screening of peptide libraries designed to combat infectious diseases and engineer the microbiome. This SuperUROP project’ s goal is to leverage machine-learning algorithms to extract structure-function relationships from the datasets generated thus far, perform biophysical and biochemical investigations, and to design next-generation peptides in silico that may serve as the basis for future medicines.
Since coming to MIT, I’ ve become very interested in the application of electrical engineering and computer science to biology. It was eye-opening to see that breakthroughs in fields such as genetics and microbiology could be attributed to principles founded in circuits or machine learning. I have participated in research that works to analyze biological systems, but look forward to working on a project where I will be creating something completely new.