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 […]