I run or better animate a ‘lab’ without benches and without a primary organism or system. The moniker ‘theoretical biology’ sends real biologists who I consort with, fleeing, and the majority of my trainees over the past 2 decades have done experiments in collaborators labs. ‘Modeling’ implies someone hands you data and you deal with it, as best possible, but people in the group did experiments precisely to get the data they needed to theorize about. ‘Data science’ is an oxymoron.
So what are the contours of my subject, call it physical biology, as I conceive it? One can divide the applications of physics to biology as overt or covert. The former would include motor proteins, ion channels, single molecule mechanics, membrane biophysics, cell motility, active matter etc, ie subjects where the physics is manifest. In recent years I have practiced the covert variety, which include models of DNA sequence inspired by statistical mechanics, models of development and cell fate derived from modern (ie post 1960, distinctly not 19th c.) mathematics and the computer science of learning theory. Generally, the motivation is to become more abstract in the hope of attaining more generality. The focus is always on mainstream biological subjects, no bio-inspired physics or niche systems: phenomena first tools second. Beware what I call the ‘hydrogen atom fallicy’. You do not get far in biology by taking a simple system (are there any really?), ignoring the genetics, biochemistry, structure, or whatever pertains, and measuring something (defined by technical feasibility) precisely. There was a period ~20y ago where molecular noise was the rage, in whatever system was at hand. What knowledge can be traced to all those papers, I am at a loss to say. Similarly, one can find data for which a Shannon entropy can be calculated from a snapshot, but the slice of phenomena thereby illuminated is small. A famous paper (Levchenko), in Science of course proved that the information content of a signaling pathway was one bit. It spawned a string of refutations that added to its citation count.
