Memorias de investigación
Ponencias en congresos:
Probabilistic Reasoning with an Enzyme-driven DNA Device
Año:2013
Áreas de investigación
  • Biocomputación,
  • Ciencias de la computación y tecnología informática
Datos
Descripción
We present a biomolecular probabilistic model driven by the action of a DNA toolbox made of a set of DNA templates and enzymes that is able to perform Bayesian inference. The model will take single-stranded DNA as input data, representing the presence or absence of a specific molecular signal (the evidence). The program logic uses different DNA templates and their relative concentration ratios to encode the prior probability of a disease and the conditional probability of a signal given the disease. When the input and program molecules interact, an enzyme-driven cascade of reactions (DNA polymerase extension, nicking and degradation) is triggered, producing a different pair of single-stranded DNA species. Once the system reaches equilibrium, the ratio between the output species will represent the application of Bayes? law: the conditional probability of the disease given the signal. In other words, a qualitative diagnosis plus a quantitative degree of belief in that diagno- sis. Thanks to the inherent amplification capability of this DNA toolbox, the resulting system will be able to to scale up (with longer cascades and thus more input signals) a Bayesian biosensor that we designed previously.
Internacional
Si
Nombre congreso
19th International Conference on DNA Computing and Molecular Programming
Tipo de participación
960
Lugar del congreso
Arizona State University, Tempe. USA.
Revisores
Si
ISBN o ISSN
978-3-319-01928-4
DOI
Fecha inicio congreso
22/09/2013
Fecha fin congreso
27/09/2013
Desde la página
160
Hasta la página
173
Título de las actas
DNA Computing and molecular programming
Esta actividad pertenece a memorias de investigación
Participantes
Grupos de investigación, Departamentos, Centros e Institutos de I+D+i relacionados
  • Creador: Grupo de Investigación: Grupo de Inteligencia Artificial (LIA)
  • Departamento: Inteligencia Artificial