Using fuzzy methods for rule extraction in the discrimination of class C GPCR subtypes from their subsequences
G-Protein-Coupled receptors (GPCR) are cell membrane proteins that regulate many of the cell functions and transduce signals between the intracellular and extracellular domains. This makes them relevant in pharmacology as therapeutic targets. As members of this superfamily, class C GPCRs in particul...
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| Tipo de recurso: | tesis de maestría |
| Fecha de publicación: | 2014 |
| País: | España |
| Institución: | Universitat Politècnica de Catalunya (UPC) |
| Repositorio: | UPCommons. Portal del coneixement obert de la UPC |
| Idioma: | inglés |
| OAI Identifier: | oai:upcommons.upc.edu:2099.1/23078 |
| Acceso en línea: | https://hdl.handle.net/2099.1/23078 |
| Access Level: | acceso abierto |
| Palabra clave: | Genomics Genòmica Àrees temàtiques de la UPC::Informàtica::Intel·ligència artificial::Sistemes experts |
| Sumario: | G-Protein-Coupled receptors (GPCR) are cell membrane proteins that regulate many of the cell functions and transduce signals between the intracellular and extracellular domains. This makes them relevant in pharmacology as therapeutic targets. As members of this superfamily, class C GPCRs in particular regulate a number of important physiological functions. Proteins of the class must be studied from their primary sequences, as only one of their 3-D structures has been fully determined, earlier this year. Protein function investigation requires the identification of motifs, or functional subsequences. In this thesis, we will describe the discrimination of class C GPCR subtypes through interpretable rules from a specific alignment free transformation of the sequences, namely amino acid composition. The Fuzzy Inductive Reasoning methodology was used as the basis to extract these linguistic rules. |
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