Predicting homologous signaling pathways using machine learning

• Author / Creator

  Bostan, Babak

• Understanding biochemical reactions inside cells of individual organisms is a key factor for improving our biological knowledge. Signaling pathways provide a road map for a wide range of these chemical reactions that convert one signal or stimulus into another. In general, each signaling pathway in a cell involves many different proteins, each with one or more specific roles that help to amplify a relatively small stimulus into an effective response. Since proteins are essential components of a cell’s activities, it is important to understand how they work – and in particular, to determine which of specie’s proteins participate in each role. Experimentally determining this mapping of proteins to roles is difficult and time consuming. Fortunately, many individual pathways have been annotated for some species, and the pathways of other species can often be inferred using protein homology and the protein properties.

• Subjects / Keywords

  • Signaling pathway
  • Machine learning
  • Support vector machine
  • Predictions

• Graduation date

  Fall 2009

• Type of Item

  Thesis

• Degree

  Master of Science

• DOI

  https://doi.org/10.7939/R3W893

• License

  This thesis is made available by the University of Alberta Libraries with permission of the copyright owner solely for non-commercial purposes. This thesis, or any portion thereof, may not otherwise be copied or reproduced without the written consent of the copyright owner, except to the extent permitted by Canadian copyright law.