Fabian Theis says quantitatively trained computational students can formalize loosely specified biological problems as metrics and develop them into models and papers.

“Then they go to a computational-- Typically, they're all computation data science type of students, right? But then they go to the computation one, they sort of get pushed the method aspect of it, and thereby sucking up a, a whole bunch of, of problems that are sort of not exactly precisely yet formulated in, in that bio lab that sort of can't directly put yet in a function.”

“But then because they are sort of methody, right, and they're quantitative, they can actually put this into a metric or whatever that then turns into a model and in a paper. And I, I think this is a way how, uh-- I mean, we've been doing this now for maybe eight years or so, this, this type of school.”