Ted Natoli
About Ted Natoli
Ted Natoli is an Associate Computational Biologist at the Broad Institute, where he has worked for over a decade. He has a strong background in bioinformatics and computational biology, with experience in developing the Connectivity Map database and expertise in various programming languages.
Current Role at Broad Institute
Ted Natoli currently serves as an Associate Computational Biologist at the Broad Institute in Cambridge, Massachusetts. He has held this position since 2012, contributing to various research initiatives in computational biology. His work involves utilizing bioinformatics tools and programming languages to analyze biological data, supporting the institute's mission to advance understanding of human health.
Previous Experience in Computational Biology
Before his current role, Ted Natoli worked at the Broad Institute as an Associate Computational Biologist II from 2012 to 2016. He also held positions at Ligon Discovery as a Bioinformatics Scientist for eight months in 2011 and as a Research Assistant from 2009 to 2011. His experience in these roles has equipped him with a robust understanding of bioinformatics and computational analysis.
Educational Background
Ted Natoli earned a Bachelor of Science degree in Biomedical Engineering from Boston University, where he studied from 2002 to 2007. He furthered his education at Harvard Extension School, focusing on Biotechnology and Bioinformatics from 2008 to 2014. This educational foundation has provided him with the necessary skills for his career in computational biology.
Contributions to Connectivity Map
Ted Natoli has contributed to the development and analysis of the Connectivity Map (CMap) database, recognized as the world's largest collection of gene expression profiles. His work in this area involves the functional annotation of perturbagens, which aids in uncovering relationships between drugs, genes, and diseases.
Technical Skills and Expertise
Ted Natoli possesses strong technical skills in Linux systems, which are essential for his computational biology research. He is proficient in various bioinformatics tools and programming languages, including Python, R, and MySQL. His expertise supports his research and enhances collaborative efforts in the scientific community.