Desarrollo de herramientas bioinformáticas para el estudio y clasificación de proteínas usando coevolución
Multiple sequence alignments (MSA) provide us with at least two types of information;\none is given by the conservation of amino acids at certain position, while the other is given by\nthe relationship or coevolution between two or more positions. This coevolution between sites\nis inferred using me...
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| Formato: | Tesis doctoral acceptedVersion |
| Lenguaje: | Español |
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Facultad de Farmacia y Bioquímica
2017
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| Acceso en línea: | http://repositoriouba.sisbi.uba.ar/gsdl/cgi-bin/library.cgi?a=d&c=posgraafa&cl=CL1&d=HWA_1813 http://repositoriouba.sisbi.uba.ar/gsdl/collect/posgraafa/index/assoc/HWA_1813.dir/1813.PDF |
| Aporte de: |
| Sumario: | Multiple sequence alignments (MSA) provide us with at least two types of information;\none is given by the conservation of amino acids at certain position, while the other is given by\nthe relationship or coevolution between two or more positions. This coevolution between sites\nis inferred using methods that estimate covariation from a MSA. In this thesis, a public webserver\ncapable of calculating covariation between residues in a protein family was developed.\nMore importantly, an interactive visualization framework is available to explore the results in\nterms of sequence conservation, covariation integrated with the protein 3D structure.\nCoevolution can also be detected at protein interfaces, where proteins need to maintain\ncertain interactions throughout their evolution. Until now, such analysis was restricted to bacterial\ngenomes sequences only and to expert users capable of building their own concatenated\nMSA suitable for this calculations. The I-COMS tools was developed to extend the analysis\nto any species as well as facilitate non expert users the calculation and interpretation of the\nobtained results. Finally, the extent of the covariation relationship across diferent protein\nfamilies was studied to assess the network topology similarity between related functional domains.\nThis study provides the foundation to the development of new methods that aim at\nclustering and classifying proteins in families. |
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