Modeling biology with solver-aided programming languages

Abstract

A good model of a biological cell exposes secrets of the cell's signaling mechanisms, explaining diseases and facilitating drug discovery. Modeling cells is fundamentally a programming problem - it's programming because the model is a concurrent program that simulates the cell, and it's a problem because it is hard to write a program that reproduces all experimental observations of the cell faithfully. In this talk, I will introduce solver-aided programming languages and show how they ease modeling biology as well as make programming accessible to non-programmers. Solver-aided languages come with constructs that delegate part of the programming problem to a constraint solver, which can be guided to synthesize parts of the program, localize its bugs, or act as a clairvoyant oracle. I will describe our work on synthesis of stem cell models in c. elegans and then show how our framework called Rosette can rapidly implement a solver aided language in several domains, from programming by demonstration to spatial parallel programming.

DOI: 10.1145/2517208.2517229

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Cite this paper

@inproceedings{Bodk2013ModelingBW, title={Modeling biology with solver-aided programming languages}, author={Rastislav Bod{\'i}k}, booktitle={GPCE}, year={2013} }