Statistical learning of biological networks: a brief overview

author: Florence d'Alche-Buc, Université Evry Val d'Essonne
published: April 17, 2008,   recorded: March 2008,   views: 417
Categories

Slides

Related content

Report a problem or upload files

If you have found a problem with this lecture or would like to send us extra material, articles, exercises, etc., please use our ticket system to describe your request and upload the data.
Enter your e-mail into the 'Cc' field, and we will keep you updated with your request's status.
Lecture popularity: You need to login to cast your vote.
  Bibliography

Description

Identification of biological networks such as signalling pathways, gene regulatory networks, protein-protein interaction networks and metabolic networks is considered as a key challenge in computational biology. Using machine learning framework, this problem can be addressed using different points of view, depending of course on the nature of the biological interactions to be inferred but also on the level of abstraction of the chosen modeling and the amount of prior knowledge available. Since 2000, research in statistical learning of biological networks have given rise to a rich panel of approaches whose interest overcomes the field of computational biology. Network identification has been tackled using large scale data-mining approaches, supervised predictive approaches and reverse-modeling approaches. In this sole last family, it is very instructive to focus on the numerous graphical models that have been proposed so far such as Graphical Gaussian Models, Bayesian networks, Dynamical Bayesian networks and state-space models. I will present a short review of these methods discussing among other issues model complexity, relevance to biology, ability to deal with hidden variables and scalability. I will also plead for the construction of a benchmark repository devoted to examples of relevant test problems even if the true relevant test has always to be made in vivo or in vitro.

See Also:

Download slides icon Download slides: licsb08_dalche_slb_01.pdf (415.9¬†KB)


Help icon Streaming Video Help

Link this page

Would you like to put a link to this lecture on your homepage?
Go ahead! Copy the HTML snippet !

Write your own review or comment:

make sure you have javascript enabled or clear this field: