4 papers
A multifactorial evaluation framework for gene regulatory network reconstruction
Laurent Mombaerts, Atte Aalto, Johan Markdahl +1
In the past years, many computational methods have been developed to infer the structure of gene regulatory networks from time-series data. However, the applicability and accuracy…
Linear system identification from ensemble snapshot observations
Atte Aalto, Jorge Goncalves
Developments in transcriptomics techniques have caused a large demand in tailored computational methods for modelling gene expression dynamics from experimental data. Recently, so-…
Continuous time Gaussian process dynamical models in gene regulatory network inference
Atte Aalto, Lauri Viitasaari, Pauliina Ilmonen +2
One of the focus areas of modern scientific research is to reveal mysteries related to genes and their interactions. The dynamic interactions between genes can be encoded into a ge…
Bayesian variable selection in linear dynamical systems
Atte Aalto, Jorge Goncalves
We develop a method for reconstructing regulatory interconnection networks between variables evolving according to a linear dynamical system. The work is motivated by the problem o…