Technological breakthroughs, including complete genomic sequencing of many species, high-throughput expression analysis, and proteomic studies are enabling exponential growth in the available biological data relevant to important biological functions. In the past, computational analysis of these burgeoning datasets has been hampered by the sparse successes in combinations of data sources, representations, and algorithms. Here we propose the application of symbolic toolsets from the formal methods community to help understand the network effects in problems of biological interest.
Unlike traditional biology that has focussed on single genes or proteins in isolation, systems biology is concerned with the study of complex interaction of many levels of biological information --- DNA, RNA, proteins, informational pathways --- to understand how they work together. Here we propose a highly automated symbolic approach to systems biology which we call Symbolic Systems Biology. Within this research program we have developed a toolset called Pathway Logic which we have applied to signaling pathways, and more specifically mammalian cell cycle control. The results of formal symbolic analysis with extremely efficient representations of biological networks provide insights with potential biological impact. In particular, novel hypotheses may be generated which can lead to wet lab validation of new signaling possibilities. We also consider the modeling and automatic analysis of multi-cellular signaling effects, exemplified by the Delta-Notch lateral inhibition mechanism. We have applied formal methods approaches to inherently continuous problems, creating discrete, completely symbolic representations which enable extremely efficient analysis of certain types of questions. In particular, we use support from decision procedures and theorem-provers to automatically generate abstractions, and then we apply state-of-the-art model-checkers to compute properties of interest. By constructing an algebra and logic of signaling pathways and creating biologically plausible abstractions, Symbolic Systems Biology provides the foundation for the application of high-powered tools such as Pathway Logic which can accelerate understanding by skilled biologists of complex biological networks.