Stage BSIB 2022-2023
Bonjour,
Merci de déposer votre/vos proposition(s) de stage pour le master BSIB 2022-2023.
Il n'y a qu'un seul formulaire pour les 3 stages :
- en M1S2 : à définir pour 2022-2023
- en M2S3 : à définir pour 2022-2023
- en M2S4 : à définir pour 2022-2023
Nous souhaitons coupler le stage M2S3 et le stage M2S4, c'est à dire que nous souhaiterions que les 2 stages se déroulent dans la même équipe sur la même thématique. Le stage M2S3 serait donc une période de préparation du stage M2S4. Cette période de stage M2S3 pourrait alors être essentiellement un travail bibliographique et de planification. C'est une recommendation pas une obligation.
pour lire les consignes concernant les 3 stages, merci de suivre les liens ci-après : M1S2, M2S3, M2S4.
Stage Master
- Stage M2S3
- Stage M2S4
Responsable de l'équipe d'accueil
Molina
Nacho
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0388653347
Personne encadrant le stage (*)
(*) modifiez si une autre personne encadre l'étudiant
Bardet
Anaïs
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0388653525
Lieu du stage
IGBMC
1 rue Laurent Fries
67400 Illkirch
1 rue Laurent Fries
67400 Illkirch
Sujet du stage
Regulation of gene expression by transcription factor binding
Multicellular organisms establish and maintain different transcriptional states in disparate cell types through complex and specific regulation of gene expression. This regulation is mediated by the cooperative binding of transcription factors (TFs) to regulatory elements through the recognition of specific DNA sequence motifs. Additionally, the physical access of transcription factors to DNA can be modulated by epigenetic regulation, such as DNA methylation, nucleosome positioning and histone modifications. Failure to maintain this tight regulation of gene expression results in developmental defects and various diseases including cancer.
During this internship, you will integrate genomic data (e.g. TF binding by ChIP-seq, gene expression by RNA-seq, chromatin accessibility by ATAC-seq) and sequence data (e.g. TF motifs) to study the sensitivity of transcription factors to DNA methylation. You will also develop deep learning approaches to better predict transcription factor binding sites in the context of DNA methylation.
You will work in an international environment at the IGBMC, a leading European institute. We are a team of computational and experimental biologists and you will benefit from the expertise in genomic data analysis (Anaïs Bardet) and modeling (Nacho Molina) for the success of the project.
During this internship, you will integrate genomic data (e.g. TF binding by ChIP-seq, gene expression by RNA-seq, chromatin accessibility by ATAC-seq) and sequence data (e.g. TF motifs) to study the sensitivity of transcription factors to DNA methylation. You will also develop deep learning approaches to better predict transcription factor binding sites in the context of DNA methylation.
You will work in an international environment at the IGBMC, a leading European institute. We are a team of computational and experimental biologists and you will benefit from the expertise in genomic data analysis (Anaïs Bardet) and modeling (Nacho Molina) for the success of the project.