Welcome to "The Digital Biologist"

With new technology comes new ways of getting stuff done and sometimes, it also creates new career possibilities as well. Just as the invention of the moving picture gave rise to the cinematographer, the technological advances that are now making it possible to model and simulate complex living systems on a computer are giving rise to a brand new profession - that of The Digital Biologist. I number myself amongst the members of this new profession and although they might not identify themselves as such, there are actually already quite a few other digital biologists out there as well. "But wait", you might be tempted to say. "Haven't people been already doing biology on computers for some time now?", to which my answer would be "Not really". Biology (with a big B) is the study of the remarkable properties of complex living systems that set them apart from all of the dead stuff of which our universe seems to be primarily composed - their ability to self-organize, to grow and reproduce, to adapt to their environments etc. etc. Until now most of the models that we have have used to describe biological systems have been essentially borrowed from the older and more established fields of physics and chemistry. In fact, although biologists often speak of relatively macroscopic concepts like reproduction and adaptation, the burgeoning wealth of data that they are producing in the laboratory is overwhelmingly physicochemical in nature. Such a detailed and microscopic description of living systems, while undoubtedly valuable, deals mostly with the kind of chemical processes that also take place in non-living systems, albeit in a far less structured and concerted manner. This data alone, captured at a scale an order of magnitude or two below that at which the actual "biology" of these systems becomes apparent, does not really describe their biology any better than a three-dimensional map of the neurons in a brain captures human consciousness.

The traditional computational models for biology borrowed from the fields of physics, chemistry and mathematics are most commonly applied at the same level of detail as the physicochemical data that is collected in the laboratory, which makes for a good fit between the modeling and the experimental work. Unfortunately however, they only allow the biologist to build either extremely detailed models of tiny portions of living systems or rather vague and low resolution models of more macroscopic regions. The convergence of ideas from the intersections of these traditional fields with computer science however, is starting to bear fruit in the form of computational modeling approaches that have been designed with the astronomical complexity of biological systems in mind and which can serve as intellectual frameworks capable of transforming this wealth of physicochemical data into real biological knowledge and insight.

For the very first time, the biologist - the digital biologist - is being presented with the opportunity to capture the essential properties and behaviors of a complex living system in a computational model that is as meaningful and relevant from a biological (with a big B) perspective as the physicist's model of an atom or the engineer's model of a suspension bridge.

Welcome to the age of the Digital Biologist!

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