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Modeling biology with solver-aided programming languages

Published:27 October 2013Publication History
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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.

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    • Published in

      cover image ACM SIGPLAN Notices
      ACM SIGPLAN Notices  Volume 49, Issue 3
      GPCE '13
      March 2014
      181 pages
      ISSN:0362-1340
      EISSN:1558-1160
      DOI:10.1145/2637365
      Issue’s Table of Contents
      • cover image ACM Conferences
        GPCE '13: Proceedings of the 12th international conference on Generative programming: concepts & experiences
        October 2013
        198 pages
        ISBN:9781450323734
        DOI:10.1145/2517208

      Copyright © 2013 Owner/Author

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      • Published: 27 October 2013

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