Add to ORKGContains fulltext : 197601.pdf (publisher's version ) (Open Access)International Conference on Probabilistic Graphical Models, 11-14 September 2018, Prague, Czech Republi
We de ne a new class of coloured graphical models, called regulatory graphs. These graphs have thei...
Thesis (Ph.D.)--University of Washington, 2016-08The recent explosion in the availability of gene ex...
Thesis (Master's)--University of Washington, 2017-06The inference of gene regulatory networks is of ...
Gene regulatory networks are a visual representation of genes and their interactions. In this visual...
Gene regulatory networks play a crucial role in controlling an organism’s biological processes, whic...
Gene regulatory networks play a crucial role in controlling an organism’s biological processes, whic...
National audienceIn this work, we reconstruct the gene regulation networks from the microarray exper...
A Bayesian network is a graph-based model of joint multivariate probability distributions that captu...
Inference about regulatory networks from high-throughput genomics data is of great interest in syste...
Bayesian network techniques have been used for discovering causal relationships among large number o...
In this paper, we present a systematic and conceptual overview of methods for inferring gene regulat...
AbstractWe define a new class of coloured graphical models, called regulatory graphs. These graphs h...
Recent advances in high-throughput molecular biology has motivated in the field of bioinformatics th...
In this chapter we discuss the advantages of the use of probabilistic graphical models for modelling...
Introduction A central goal of molecular biology is to understand the regulatory interactions of ge...
We de ne a new class of coloured graphical models, called regulatory graphs. These graphs have thei...
Thesis (Ph.D.)--University of Washington, 2016-08The recent explosion in the availability of gene ex...
Thesis (Master's)--University of Washington, 2017-06The inference of gene regulatory networks is of ...
Gene regulatory networks are a visual representation of genes and their interactions. In this visual...
Gene regulatory networks play a crucial role in controlling an organism’s biological processes, whic...
Gene regulatory networks play a crucial role in controlling an organism’s biological processes, whic...
National audienceIn this work, we reconstruct the gene regulation networks from the microarray exper...
A Bayesian network is a graph-based model of joint multivariate probability distributions that captu...
Inference about regulatory networks from high-throughput genomics data is of great interest in syste...
Bayesian network techniques have been used for discovering causal relationships among large number o...
In this paper, we present a systematic and conceptual overview of methods for inferring gene regulat...
AbstractWe define a new class of coloured graphical models, called regulatory graphs. These graphs h...
Recent advances in high-throughput molecular biology has motivated in the field of bioinformatics th...
In this chapter we discuss the advantages of the use of probabilistic graphical models for modelling...
Introduction A central goal of molecular biology is to understand the regulatory interactions of ge...
We de ne a new class of coloured graphical models, called regulatory graphs. These graphs have thei...
Thesis (Ph.D.)--University of Washington, 2016-08The recent explosion in the availability of gene ex...
Thesis (Master's)--University of Washington, 2017-06The inference of gene regulatory networks is of ...