After leaving the N.I.H., I ended up in my current role, where I work on developing computational pipelines and tools for target discovery in various cancers.
SG: Growing up, I wanted to be a doctor. As I completed my schooling, I was interested in languages, Science and Mathematics. I then developed more interest in analytical skills. In those days, bioinformatics was relatively new. I finished my bachelor’s and Master’s degree in physics. I was interested in quantum mechanics and non-linear dynamics. For my project, I was interested in developing an algorithm for the optimization of structures (arrangement of atoms in space for lowest energy) using Genetic Algorithm (machine learning). This project extended to small peptides, and this is how I began my journey in bioinformatics.
What are some typical day-to-day responsibilities you have, or decisions you make?
SS: The day-to-day responsibilities and decisions that I make vary, which makes the job interesting. Much of my time is spent using various computational tools and methods to analyze large datasets, identifying patterns and trends to understand biological processes, developing custom scripts and programs to automate data analysis and processing tasks, and developing software tools other colleagues can use to analyze or manage data. Besides the computational responsibilities, I’m involved in facilitating collaborations with different departments and organizations, so I spend a lot of time deciding how to best communicate results to experts and non-experts.
SG: Most of my work hours are spent writing computational scripts and analyzing sequenced data.
