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Predicting homologous signaling pathways using machine learning

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 cells activities, it is important to understand how they work and in particular, to determine which of species 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.

Identiferoai:union.ndltd.org:LACETR/oai:collectionscanada.gc.ca:AEU.10048/738
Date11 1900
CreatorsBostan, Babak
ContributorsGreiner, Russell (Computing Science), Szafron, Duane (Computing Science), Gallin, Warren (Cell Biology), Holte, Robert (Computing Science)
Source SetsLibrary and Archives Canada ETDs Repository / Centre d'archives des thèses électroniques de Bibliothèque et Archives Canada
LanguageEnglish
Detected LanguageEnglish
TypeThesis
Format1184912 bytes, application/pdf

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