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Recolector de Ciencia Abierta, RECOLECTA
Doctoral thesis . 2019
License: CC BY NC ND
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
Recolector de Ciencia Abierta, RECOLECTA
Doctoral thesis . 2020
License: CC BY NC ND
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
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Multi-omics integration for biomarker discovery

Authors: Clos García, Marc;

Multi-omics integration for biomarker discovery

Abstract

Los estudios de identificación de nuevos biomarcadores reciben una cantidad notable de financiación, pero su éxito es reducido, con solo un 0.1% de los nuevos biomarcadores identificados llegando a implantarse en la práctica clínica rutinaria. Las tecnologías de alto rendimiento (ómicas) permiten la medición de una cantidad muy elevada de variables, facilitando así la posible identificación de nuevos biomarcadores. Los desarrollos tecnológicos más recientes han permitido abaratar sus costes, facilitando así la implantación y globalización de este tipo de estudios. A su vez, esto ha supuesto un incremento en el número de candidatos a biomarcador que no superan las fases de validación, en parte por la falta de protocolos y métodos de análisis estandarizados y robustos para este tipo de datos. En esta tesis, hemos estudiado qué métodos son más eficientes en la identificación de biomarcadores derivados de la combinación de distintas ómicas, principalmente microbioma y metabolómica. Nos hemos centrado en la identificación de nuevos biomarcadores diagnósticos para tres enfermedades con un elevado impacto socioeconómico: el cáncer de próstata, el cáncer colorectal y la fibromialgia. Para todos los potenciales biomarcadores identificados hemos estudiado su robustez y capacidad predictiva mediante una combinación de métodos bioinformáticos y experimentales, para tratar de aportar biomarcadores capaces de superar la fase de validación correspondiente con éxito.

Los capítulos 5 y 6 están sujetos a confidencialidad por el autor. 235 p.

CICbioGUNE BioDonostia

Country
Spain
Keywords

data analysis, mass spectroscopy, molecular biology, análisis de datos, espectroscopia de masas, biología molecular

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green