His paper Abstract Machines of Systems Biology [1] is a wonderful, only slightly outdated, of what the field might be able to achieve in the future.

I think and hope program analysis, abstract interpretation and friends will make a comeback to biology. Definitely topics covered in CS not in bioinformatics, which IMHO tends to be too applied for a first or second degree. I'd rather stick to the basics.

[1] http://lucacardelli.name/Papers/Abstract%20Machines%20of%20S...

Probabilistic model checking of (models of) biological systems is definite done by Luca's group:

- Design and Analysis of DNA Strand Displacement Devices using Probabilistic Model Checking http://lucacardelli.name/Papers/Design%20and%20Analysis%20of...

- Central Limit Model Checking http://lucacardelli.name/Papers/Central%20Limit%20Model%20Ch...

It varies from place to place, the better schools generally offer a more rigorous combination of CS and Biology, the reason why it may appear applied is mostly because Bioinformatics offered on MOOCS like EdX tend to only offer courses that fall under its specific subject code, giving the impression the entire field is about string manipulation. This is the same with other interdisciplinary subjects like mechatronics, they are generally a combination of two majors but courses exclusive to the particular interdisciplinary subject are lot more rare. Computational biology is a lot more than string processing and crunching through PDEs (synthetic biology), there is a tremendous amount of machine learning used in the current state of the art proteomics and drug synthesis research.

Totally agree. I think his paper "Can a Systems Biologist Fix a Tamagotchi?" is really nice, shows some of the fundamental conceptional issues and very fun reading nonetheless: http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.131...