From transcriptomics to proteomics: Unraveling biological knowledge via Machine Learning

  1. Serrano-Sanz, Guillermo
Dirigida por:
  1. Mikel Hernáez Director
  2. Elizabeth Guruceaga Directora

Universidad de defensa: Universidad de Navarra

Fecha de defensa: 20 de diciembre de 2022

Tribunal:
  1. Antonio Pineda Lucena Presidente
  2. Silvestre Vicent Cambra Secretario/a
  3. Enrique Santamaría Martínez Vocal
  4. Ian Michael Traniello Vocal
  5. David Gómez Cabrero Vocal

Tipo: Tesis

Teseo: 783274 DIALNET lock_openDadun editor

Resumen

We start by highlighting basic concepts of both molecular biology and machine learning. This overview focuses on the key ideas that are required to comprehend the rest of the work, and thus, it does not attempt at providing a comprehensive review. We start with the basis of DNA and RNA, the genetic building bricks, until the formation of the proteins, the final actors of the genetic machinery. We also explore state-of-the-art technologies to measure those processes along with their limitations. After introducing the basic biological concepts, we will discuss the basics of machine learning methodologies and some of the most important models used in recent years to solve many biological problems.