SGAI

UK Symposium on Knowledge Discovery
and Data Mining 2020

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Dr. Tom Thorne, University of Reading

Learning and analysing networks from biological data

Abstract

High throughout experimental methods allow data to be collected that can be used to infer the network structures of biological systems. We discuss several methods for learning networks from biological data, applying fast approximate Bayesian inference methods, that can generate new understanding of biological systems. One challenge is in deriving relevant biological insights from these networks, and to do so we apply differential network inference to identify changes between different experimental conditions. We also consider the problem of learning communities in biological networks where the structure of the network is known, incorporating covariates that represent our knowledge of the properties of the individual network nodes.

SGAI

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