In the present contribution we provide a discussion of the paper on “Bayesian graphical models for modern biological applications”. The authors present an extensive review of Bayesian graphical models, which are used for a variety of inferential tasks applied to biology and medicine settings. Our contribution proposes a conceptual connection between two scientific frameworks, graphical models and social network analysis, by highlighting also the role played by network models and random graphs. A bibliometric analysis is performed by exploiting publications collected from online bibliographic archives to map the main themes characterizing the two research fields. Specifically, a co-word network analysis is carried out using visualization too...
This chapter introduces a probabilistic approach to modelling in physiology and medicine: the quanti...
Gene regulatory networks are a visual representation of genes and their interactions. In this visual...
Abstract. This paper introduces graphical models as a natural environment in which to formulate and ...
In the present contribution we provide a discussion of the paper on “Bayesian graphical models for m...
In the present contribution we provide a discussion of the paper on ‘‘Bayesian graphical models for...
In the present contribution we provide a discussion of the paper on ‘‘Bayesian graphical models for...
In the present contribution we provide a discussion of the paper on ‘‘Bayesian graphical models for...
In the present contribution we provide a discussion of the paper on ‘‘Bayesian graphical models for...
In the present contribution we provide a discussion of the paper on ‘‘Bayesian graphical models for...
The aim of this chapter is twofold. In the first part we will provide a brief overview of the mathem...
In this work, we propose approaches for the inference of graphical models in the Bayesian framework....
We contribute to the discussion of the paper by Ni et al. (Stat Methods Appl, 2021. https://doi...
In this chapter we discuss the advantages of the use of probabilistic graphical models for modelling...
In this chapter we discuss the advantages of the use of probabilistic graphical models for modelling...
This chapter introduces a probabilistic approach to modelling in physiology and medicine: the quanti...
This chapter introduces a probabilistic approach to modelling in physiology and medicine: the quanti...
Gene regulatory networks are a visual representation of genes and their interactions. In this visual...
Abstract. This paper introduces graphical models as a natural environment in which to formulate and ...
In the present contribution we provide a discussion of the paper on “Bayesian graphical models for m...
In the present contribution we provide a discussion of the paper on ‘‘Bayesian graphical models for...
In the present contribution we provide a discussion of the paper on ‘‘Bayesian graphical models for...
In the present contribution we provide a discussion of the paper on ‘‘Bayesian graphical models for...
In the present contribution we provide a discussion of the paper on ‘‘Bayesian graphical models for...
In the present contribution we provide a discussion of the paper on ‘‘Bayesian graphical models for...
The aim of this chapter is twofold. In the first part we will provide a brief overview of the mathem...
In this work, we propose approaches for the inference of graphical models in the Bayesian framework....
We contribute to the discussion of the paper by Ni et al. (Stat Methods Appl, 2021. https://doi...
In this chapter we discuss the advantages of the use of probabilistic graphical models for modelling...
In this chapter we discuss the advantages of the use of probabilistic graphical models for modelling...
This chapter introduces a probabilistic approach to modelling in physiology and medicine: the quanti...
This chapter introduces a probabilistic approach to modelling in physiology and medicine: the quanti...
Gene regulatory networks are a visual representation of genes and their interactions. In this visual...
Abstract. This paper introduces graphical models as a natural environment in which to formulate and ...