Skip to Main content Skip to Navigation
Theses

Vérification formelle et apprentissage logique pour la modélisation qualitative à partir de données single-cell

Abstract : The understanding of cellular mechanisms occurring inside human beings usually depends on the study of its gene expression.However, genes are implied in complex regulatory processes and their measurement is difficult to perform. In this context, the qualitative modeling of gene regulatory networks intends to establish the function of each gene from the discrete modeling of a dynamical interaction network. In this thesis, our goal is to implement this modeling approach from single-cell sequencing data. These data prove to be interesting for qualitative modeling since they bring high precision, and they can be interpreted in a dynamical way. Thus, we develop a method for the inference of qualitative models based on the automatic learning of logic programs. This method is applied on a single-cell dataset, and we propose several approaches to interpret the resulting models by comparing them with existing knowledge.
Document type :
Theses
Complete list of metadata

https://tel.archives-ouvertes.fr/tel-03717511
Contributor : ABES STAR :  Contact
Submitted on : Friday, July 8, 2022 - 11:26:25 AM
Last modification on : Friday, August 5, 2022 - 2:54:52 PM

File

S_BUCHET.pdf
Version validated by the jury (STAR)

Identifiers

  • HAL Id : tel-03717511, version 1

Citation

Samuel Buchet. Vérification formelle et apprentissage logique pour la modélisation qualitative à partir de données single-cell. Apprentissage [cs.LG]. École centrale de Nantes, 2022. Français. ⟨NNT : 2022ECDN0011⟩. ⟨tel-03717511⟩

Share

Metrics

Record views

1

Files downloads

0