As Melanie Mitchell, an expert on such adaptive computation, puts it: "Biological evolution is an appealing source of inspiration for addressing these problems. Evolution is, in effect, a method of searching among an enormous number of possibilities for 'solutions.' "
In borrowing the notion, the computational methods even take analogous terms like "chromosome" (for a candidate solution), "gene" (for the encoding bit or bits that yield a part of the solution), and "mutation" (the deliberately random changing of a piece in the processing to see potential variations in a puzzle's ultimate assembly).
As computing benefits from mimicking the way biology works, mathematics and computational algorithms are being applied in innovative ways to advance understanding of biology. The field of bioinformatics, for example, uses high-level mathematics to analyze the chemical structure and functions of genes.
However, much of medium-scale biology has, by and large, missed the benefits of these and other algorithms. That could begin to change with "The Roles of Mathematics and Computation in Systems and Integrative Biology," a workshop being held today and tomorrow, March 27-28, at Utah State University sponsored by the National Science Foundation (NSF).
At the Logan campus, Mitchell and 20 other biologists, mathematicians and engineers are exploring how such computational innovations can lead to a greater understanding of how the components of life interact at levels larger than chromosomes and smaller than populations -- or generally in the context of cells, organs and organisms.
The scientists, many of them researchers supported by NSF, are examining the bio-derived methods and other mathematical and computational tools not
Contact: Sean Kearns
National Science Foundation