Chromatin organization: 
Meta-analysis for the identification and classification of structural patterns

• Autores: Silvia Galan Martínez
• Directores de la Tesis: Marc A. Marti-Renom (dir. tes.), Francois Serra (codir. tes.)
• Lectura: En la Universitat Pompeu Fabra ( España ) en 2020
• Idioma: español
• Tribunal Calificador de la Tesis: Luciano Di Croce (presid.), Sandra Peiro Sales (secret.), Ralph Stadhouders (voc.)
• Materias:
  • Matemáticas
    • Ciencia de los ordenadores
      • Inteligencia artificial
  • Física
    • Física atómica y nuclear
      • Estructura nuclear
  • Ciencias de la vida
    • Biología molecular
• Enlaces
  • Tesis en acceso abierto en: TDX
• Resumen

  • High-throughput Chromosome Conformation Capture (3C) experiments, provide detailed three-dimensional (3D) information about genome organization. Specially, Hi-C, a 3C derivative, has become the standard technique to investigate the 3D chromatin structure, and its functional implication into cell fate determination. However, the correct bioinformatic analysis and interpretation of this data is still an active field of development.

    In this thesis, we explore the ability of CTCF to form chromatin loops and their epigenetic signature, by developing Meta-Waffle, an artificial neural network to classify structural patterns without any prior information. This classification, was used to generate a convolutional neural network to de novo detect chromatin loops from Hi-C contact matrices, called LOOPbit.

    We also present CHESS, a bioinformatic tool for the comparison of chromatin contact maps and differential 3D feature extraction, such as Topologically Associating Domains, stripes or loops.