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6 results on '"Menolascina F"'

1. Bayesian model selection in synthetic biology: factor levels and observation functions⁎⁎This project is partially supported by EC funding 766840-COSY-BIO, an EPSRC Innovation Fellowship (EP/S001921/1) and an EPSRC New Investigator Award (EP/R035350/1); L.B. is supported by EPSRC funding EP/P017134/1-CONDSYC; EBC acknowledges funding from Spanish MINECO, grant refs. AGL2015-67504-C3-2-R and RTI2018-093744-B-C33.

Author

Bandiera, L., Gomez Cabeza, D., Balsa-Canto, E., and Menolascina, F.

Abstract

Data-driven inference of the most plausible mechanistic model within a set of candidates is a major hurdle in synthetic and systems biology. Probabilistic model selection is hampered by limitations in the quality and amount of biological data. Furthermore, the computational cost of discriminating between competing models often leads the user to skip model selection and subjectively choose a model.

Published
2019
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