Abstract
While the “sequence” and “structure” branches of molecular biology are successfully consolidating their knowledge in a uniform and easily accessible manner, the mountains of knowledge regarding the function, activity and interaction of molecular systems in the cell remain fragmented. The reason is the adoption of good abstractions - “DNA-as-string” and “Protein-as-3D-labeled-graph” - in sequence and structure research, respectively, and the lack of a similarly successful abstraction in molecular systems research. We believe that computer science is the right place to search for this much needed abstraction. In particular, we believe that the “Molecule-as-computation” abstraction could be the basis for consolidating the knowledge of biomolecular systems. With such an abstraction, a system of interacting molecular entities is viewed as, and is described and modeled by, a system of interacting computational processes. Basic molecular entities are described by primitive processes and complex entities are described hierarchically, through process composition. For example, if a and b are abstractions of two molecular domains of a single molecule, then (a parallel b) is an abstraction of the corresponding two-domain molecule. Similarly, if a and b are abstractions of the two possible behaviors of a molecule that can be in one of two conformational states, depending on the ligand it binds, then (a choice b) is an abstraction of the molecule, with the behavioral choice between a and b determined by its interaction with a ligand process. We note that this abstraction is similar to cellular automata in that the behavior of a system emerges from the composition of interacting computational entities, but differs in that the computational entities are abstractions of mobile molecular entities rather than of static portions of space.
Joint work with Aviv Regev and Bill Silverman.
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© 2002 Springer-Verlag Berlin Heidelberg
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Shapiro, E. (2002). Invited Lecture — Molecule as Computation: Towards an Abstraction of Biomolecular Systems. In: Guigó, R., Gusfield, D. (eds) Algorithms in Bioinformatics. WABI 2002. Lecture Notes in Computer Science, vol 2452. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45784-4_31
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DOI: https://doi.org/10.1007/3-540-45784-4_31
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