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5.1 Manejo de datos genómicos para diagnóstico y toma de decisiones en la práctica clínica
Página Principal
Cursos
2025
Módulo 5
5.1 Diagn. y toma de decisiones
MÓDULO 3
Piñeiro-Yáñez E, et al. PanDrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data. Genome Med. 2018 May 31;10(1):41.
Salta al contenido principal
Piñeiro-Yáñez E, et al. PanDrugs: a novel method to prioritize anticancer drug treatments according to individual genomic data. Genome Med. 2018 May 31;10(1):41.
Haga clic en
Piñeiro-Yañezetal.GenomeMed.2019.pdf
para ver el archivo.
◄ Lectura del artículo: “Whole genome sequencing in clinical practice”,
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Avisos
Cuestionario de expectativas
Cuestionario de conocimientos previos
Avisos
El papel del Big Data en la medicina de precision
Dopazo J, et al. Implementing Personalized Medicine in COVID-19 in Andalusia: An Opportunity to Transform the Healthcare System. J Pers Med. 2021 May 26;11(6):475
Using FastQC to check the quality of high throughput sequence. Caso práctico [Video]
Herramienta FASTQC
Lectura de artículo: “Variant calling: Considerations, practices and developments”,
Lectura del artículo “Advancing Access to genome sequencing for rare genetic disorders: recent progress and call to action”
Lectura del artículo: “Whole genome sequencing in clinical practice”,
Lectura del artículo “Structural variant detection in cancer genomes: computational challenges and perspectives for precision oncology”,
Introducción a una de las tecnologías emergentes para la detección de variantes estructurales, 10x linked-reads:
Lectura del artículo “A crowdsourcing database for the copy-number variation of the Spanish population”,
Caso práctico NEXTSTRAIN
Lectura del artículo “Enhancing SARS-CoV-2 surveillance through regular genomic sequencing in Spain: The RELECOV Network”
Lectura del artículo “Detection of High Level of Co-Infection and the Emergence of Novel SARS Cov-2 Detal-Omicron and Omicron-Omicron Recombinants in the Epidemiological Surveillance of Andalusia”,
Lectura del artículo “Ten recommendations for supporting open pathogen genomic analysis in public health”,
Casimiro-Soriguer CS,et al. Antibiotic resistance and metabolic profiles as functional biomarkers that accurately predict the geographic origin of city metagenomics samples. Biol Direct. 2019 Aug 20;14(1):15.
Casimiro-Soriguer CS, Loucera C, Peña-Chilet M, Dopazo J. Towards a metagenomics machine learning interpretable model for understanding the transition from adenoma to colorectal cancer. Sci Rep. 2022 Jan 10;12(1):450.
Méndez-Salazar EO, et al. Taxonomic variations in the gut microbiome of gout patients with and without tophi might have a functional impact on urate metabolism. Mol Med. 2021 May 24;27(1):50.
Thomas AM, Manghi P, et al. Metagenomic analysis of colorectal cancer datasets identifies cross-cohort microbial diagnostic signatures and a link with choline degradation. Nat Med. 2019 Apr;25(4):667-678. ¡
Wirbel J,et al. Meta-analysis of fecal metagenomes reveals global microbial signatures that are specific for colorectal cancer. Nat Med. 2019 Apr;25(4):679-689.
Caso práctico 1
Caso práctico 2
Bioinformatics of germline variant discovery for rare disease diagnostics: current approaches and remaining challenges.
Best practices for the interpretation and reporting of clinical whole genome sequencing.
Resources and tools for rare disease variant interpretation.
Datos secuenciación
Examen Final
Encuesta de satisfacción del curso
Encuesta de evaluación a los docentes
Encuesta de evaluación de los docentes
Lectura del artículo “Structural variant detection in cancer genomes: computational challenges and perspectives for precision oncology”, ►
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