1 citations · 1 across the 4 of their papers we have counts for
4 papers
Reliable model selection in the presence of parameter non-identifiability
Yong See Foo, Torkel E. Loman, Alexander P. Browning +3
Mathematical models are invaluable for understanding and predicting how biological systems behave, although their construction requires specifying mechanisms and relationships that…
Quantifying structural uncertainty in chemical reaction network inference
Yong See Foo, Adriana Zanca, Jennifer A. Flegg +1
Dynamical systems in biology are complex, and one often does not have comprehensive knowledge about the interactions involved. Chemical reaction network (CRN) inference aims to ide…
Haplotype frequency inference from pooled genetic data with a latent multinomial model
Yong See Foo, Jennifer A. Flegg
In genetic studies, haplotype data provide more refined information than data about separate genetic markers. However, large-scale studies that genotype hundreds to thousands of in…
A Comparison of Bayesian Inference Techniques for Sparse Factor Analysis
Yong See Foo, Heejung Shim
Dimension reduction algorithms aim to discover latent variables which describe underlying structures in high-dimensional data. Methods such as factor analysis and principal compone…