 |
|
| HAL: hal-00484705, version 1 |
| Detailed view |  Export this paper |
 |
| Proc. SFC 2010, XVIIth Join Meeting of the French Society of Classification, France, Saint-Denis de la Réunion, 9-11 june, Saint-Denis de la Réunion : France (2010) |
|
|
|
|
| Réseaux bayésiens hiérarchiques avec variables latentes pour la modélisation des dépendances entre SNP: une approche pour les études d'association pangénomiques |
|
|
| Raphaël Mourad 1Christine Sinoquet 1 |
|
|
| For the BIL Bioinformatics Research Project of Pays de la Loire Region, France collaboration(s) |
|
|
| (2010-06-09) |
|
|
|
| Discover the genetic basis of common genetic diseases represents a public health issue. However this task presents several difficulties such as high data dimensionality and identification of the causal mutations. For this purpose, the modelling of dependencies between genetic markers using hierarchical bayesian networks offers several possibilities: data dimension reduction through latent variables and identification of causal markers through the conditional independence property. |
|
|
|
|
|
|
|
|
|
|
|
| 1: | Laboratoire d'Informatique de Nantes Atlantique (LINA) |
|
|
|
CNRS : UMR6241 – Université de Nantes – École Nationale Supérieure des Mines - Nantes |
|
|
|
|
|
|
|
|
|
| Subject | : | Computer Science/Bioinformatics Life Sciences/Quantitative Methods |
|
|
| Bayesian networks – hierarchical latent class model – data dimensionality reduction – genetic marker dependency modelling – genome-wide association study |
|
|
|
| Attached file list to this document: | |||||
|
|||||
|
|
|
| hal-00484705, version 1 | |
| http://hal.archives-ouvertes.fr/hal-00484705 | |
| oai:hal.archives-ouvertes.fr:hal-00484705 | |
| From: Christine Sinoquet | |
| Submitted on: Tuesday, 18 May 2010 19:46:41 | |
| Updated on: Tuesday, 18 May 2010 21:42:10 | |
