MOFA is a factor analysis model that provides a general framework for the integration of multi-omic data sets in a completely unsupervised fashion. Intuitively, MOFA can be viewed as a versatile and ...

The analysis in this article does not use actual data obtained directly from note. I have used simulation data (n=500) generated in Python based on parameters set by the author using prior research ...

aSchool of Biomedical Engineering and Imaging Sciences, King's College London, London, UK ...

In the early 1970s, statisticians had difficulty in analysing data where the random variation of the errors did not come from the bell-shaped normal distribution. Besides normality, these traditional ...

StateSpaceDynamics.jl is a comprehensive and self-contained Julia package for working with probabilistic state space models (SSMs). It implements a wide range of state-space models, taking inspiration ...

Predictive microbiology models explain bacterial number variations over time and how growth/inactivation rates are affected by environmental conditions (Lammerding and Fazil, 2000). In the development ...

Fluorescence lifetime imaging (FLI), although capable of providing powerful biomedical insight, necessitates computationally expensive inverse solvers to obtain parameters of interest, which has ...