I am Anurag Limdi, a Data Scientist at Apriori Bio, where I integrate machine learning and analyses of deep mutational scanning experiments of proteins to understanding genotype to phenotype mapping and inform vaccine design for infectious diseases.
Research Interests
These days, I think about problems that span molecular evolution, protein design, and applying machine learning to problems in biology. Trained as a systems biologist at the intersection of computational and lab science, I believe in deeply understanding the quirks and biases in biological datasets, particularly large genomics datasets, in order to build generalizable models.
My PhD Research
I got my PhD at Harvard with Michael Baym, I explored how bacterial genomes function and evolve, through a combination of high-throughput experiments, theory and computational approaches. My projects include:
- Mapping fitness landscapes over thousands of generations of the long-term evolution experiment, published in Science as co-first author (Paper, Code). Our paper got featured in Nature Reviews Genetics and I chatted with ScienceAdviser about what we found and implications for the field of evolutionary biology.
- Fitness assay design using theory, Monte-Carlo simulations to explore tradeoffs in design parameters (Paper, Code).
- Methods development for correcting for PCR-related artifacts in transposon sequencing experiments (Code).
- Modeling DNA-binding biases of the mariner transposon (Code).