Humans are animals, and humans invented programming. Therefore, programming is applied biology.

Science researchers and students often spend a lot of their time doing statistical analysis, including using programming for that.

Bayesian analysis of complex intelligent systems via friston's free energy principle and active inference? Or machine learning?

Personally love the stuff circling Michael Levin at tufts university. I could also imagine there's a lot of unique model building in different biological/ecological niches.

Computational biology and ecology are a huge part of those fields. I work at a research lab (in computer science) and one of our sister labs is dedicated to environmental stuff and has mostly biologists and ecologists employed at it; a large part of the research they do involves supercomputing somehow, so we tend to partner with them a lot. As an example, modeling population growth or decline due to a change in the population's environment is one such use of computing and statistics in biology and ecology.

lm(turtle_gender ~ temp, data = data_frame)

Probably Python and R for statistical analysis, which is common nowadays in most empirical sciences.