Soutenance de These: « Predicting the natural yeast phenotypic landscape with machine learning » Sakshi KHAIWAL
Faculté de Médecine - Salle ED 12/13Directeur de thèse : Gianni LITI
Directeur de thèse : Gianni LITI
Thesis director: Gaël CRISTOFARI Abstract : A major part of gene introns contains cryptic splicing, termination signals, and abundant DNA and RNA protein-binding sites. These sequences are often found in mobile DNA units known as transposable elements embedded in long genes. These sequences could interfere with the transcription elongation of the genes in which they […]
Amphithéâtre du CAL Thesis directors : Aldine AMIEL & Eric RÖTTINGER Abstract : Regeneration is a biological process that enables organisms to replace lost or damaged tissues, organs, or entire body parts. While regeneration shares common cellular and molecular mechanisms across species, its extent and efficiency vary widely. In the context of my PhD, I investigated […]
Thesis directors: Sylvie BANNWARTH, Silvia BOTTINI Abstract: Mitochondrial diseases (MDs) are a group of rare and highly heterogeneous disorders caused by dysfunction of the mitochondria, the cellular organelles responsible for energy production. These diseases can result from variants in either the nuclear or mitochondrial genome and affect virtually any organ system, leading to a broad […]