Prediction of inherited and genetic mutations using the software model checker SPIN

  • Authors:

  • Zubin Balsara;Steve Roach

  • Affiliations:

  • University of Texas at El Paso El Paso, Texas;University of Texas at El Paso El Paso, Texas

  • Venue:
  • Proceedings of the 2005 ACM symposium on Applied computing
  • Year:
  • 2005

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Abstract

Genetic testing is becoming an important tool for detection of many genetic diseases. Designing a genetic test requires accurate data and an efficient means of comparing sequences that are present in the databases. However, as prodigious amount of data continue to emerge, querying the database to make important predictions is becoming arduous. It is essential that better tools be designed to analyze these data. In this paper, a model-based approach to gene tests and the analysis of metabolic pathways is proposed. Gene sequences and metabolic processes are modeled using formal language, and predictions are made through the verification mechanism of a software model checker. The technique is demonstrated with models of genes for cystic fibrosis tranmembrane conductance regulator protein and the map kinase pathway.