In the course of compiling this survey, several investigators remarked that it tends to be easier for computer scientists to learn biology than for biologists to learn computer science. Even so, it is hard to believe that learning the central dogma and the Krebs cycle will enable your typical programmer-turned-computational-biologist to stumble upon a project that yields important novel biological insights. So what characterizes successful computational biologists?

George Church, whose laboratory at Harvard Medical School (Cambridge, MA, USA) has a history of producing bleeding-edge research in many cross-disciplinary domains, including computational biology, says, “Individuals in my lab tend to be curious and somewhat dissatisfied with the way things are. They are comfortable in two domains simultaneously. This has allowed us to go after problems in the space between traditional research projects.” A former Church lab member, Greg Porreca, articulates this idea further: “I've found that many advances in computational biology start with simple solutions written by cross-functional individuals to accomplish simple tasks. Bigger problems are hard to address with those rudimentary algorithms, so folks with classical training in computer science step in and devise highly optimized solutions that are faster and more flexible.”

An overarching theme that also emerges from this survey suggests that tools for computational analyses permeate biological research according to three stages: first, a cross-functional individual sees a problem and devises a solution good enough to demonstrate the feasibility of a type of analysis; second, robust tools are created, often utilizing the specialized knowledge of formally trained computer scientists; and third, the tools reach biologists focused on understanding specific phenomena, who incorporate the tools into everyday use. These stages echo existing broader literature on disruptive innovations1 and technology-adoption life cycles2,3, which may suggest how breakthroughs in computational biology can be nurtured.