From genotype to phenotype: computational approaches for inferring microbial traits relevant to the food industry

Abstract

This was the first publication that I was a part of in my job as a scientist in Chr. Hansen (now Novonesis), a company that produces bacterial cultures for the food industry. Here we present a review of the main computational approaches for inferring phenotype from genotype. We divided all aproaches in 3 categories: knowledge-driven (where you build models from known mechanisms based on e.g. literature sources), data-driven (where you infer mechanisms from data using e.g. machine learning), and hybrid appraoches that combine both knowledge and data-driven aspects. I was in charge of compiling all these hybrid approaches, and it was a good oportunity for me to learn more about the state of the art of the field.

Benjamín J. Sánchez

Senior Scientist

Biology, math, programming, running, and many other fun things