Abstract
We present a computing model based on the DNA strand displacement technique which performs Bayesian inference. The model will take single stranded DNA as input data, representing the presence or absence of a specific molecular signal (evidence). The program logic encodes the prior probability of a disease and the conditional probability of a signal given the disease playing with a set of different DNA complexes and their ratios. When the input and program molecules interact, they release a different pair of single stranded DNA species whose relative proportion represents the application of Bayes’ Law: the conditional probability of the disease given the signal. The models presented in this paper can empower the application of probabilistic reasoning in genetic diagnosis in vitro.
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Sainz de Murieta, I., Rodríguez-Patón, A. (2012). Probabilistic Reasoning with a Bayesian DNA Device Based on Strand Displacement. In: Stefanovic, D., Turberfield, A. (eds) DNA Computing and Molecular Programming. DNA 2012. Lecture Notes in Computer Science, vol 7433. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32208-2_9
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DOI: https://doi.org/10.1007/978-3-642-32208-2_9
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