review articles

Doi: 10.1145/1506409.1506427

The convergence of CS and biology will serve
both disciplines, providing each with greater
power and relevance.
BY coRRaDo PRiami
algorithmic
systems
Biology
throughout the hiStory

of computer science, leading
researchers—including Turing, von Neumann, and
Minsky—have looked to nature. This inspiration
has often led to extraordinary results, some of which
acknowledged biology even in their names: cellular
automata, neural networks, and genetic algorithms, for
example.

Computing and biology have been converging ever more closely for the past two decades, but with a vision of computing as a resource for biology. The resulting field of bioinformatics addresses structural aspects of biology, and it has produced databases, pattern manipulation and comparison methods, search tools, and data-mining techniques. ^{47, 48} Bioinformatics’ most notable and successful application so far has been the Human Genome Project, which was made possible by the selection of the correct abstraction for representing DNA (a language with a four-character alphabet). ⁴⁸ But things are now proceeding in the reverse direction as well. Biology is experiencing a heightening of

interest in system dynamics by interpreting living organisms as information manipulators. 30 It is thus moving toward “systems biology.” ³¹ There is no general agreement on systems biology’s definition, but whatever we select must embrace at least four characterizing concepts. Systems biology is a transition:

˲ From qualitative biology toward a quantitative science;

˲ From reductionism to system-level understanding of biological phenomena;

˲From structural and static descriptions to functional and dynamic properties; and

˲ From descriptive biology to mecha-nistic/causal biology.

These features highlight the fact that causality between events, the temporal ordering of interactions and the spatial distribution of components are becoming essential to addressing biological questions at the system level. This development poses new challenges to describing the step-by-step mechanistic components of phenotypical phenomena, which bioinformatics does not address. ⁹

One of the philosophical foundations of systems biology is mathematical modeling, which specifies and tests hypotheses about systems; ⁷ it is also a key aspect of computational biology because it deals with the solution of systems of equations (models) through computer programs. ³⁷ Solution of systems of equations is sometimes termed “simulation.” By whatever name, the main concept to be exploited involves instead algorithms and the ( programming) languages used to specify them. We can then recover temporal, spatial, and causal information on the modeled systems by using well-established computing techniques that deal with program analysis, composition, and verification; integrated software-development environments; and debugging tools as well as computational complexity and algorithm animation. The convergence between computing and systems biology on a peer-to-peer basis is then a valuable opportunity that can