The course offers advanced models for the analytics and visualisation of complex data. These are unconventional models based on AI techniques, such as machine learning or deep learning. The topics covered in the course provide a practical and up-to-date overview of the most common bioinformatics methods and tools for the study of genomes, transcriptomes and metagenomes. Fundamental aspects such as sequence processing and quality control, the use of genomic databases, the management of high-performance computational resources (clusters), as well as the interpretation of results in different research contexts, from basic science to clinical and biotechnology applications, are covered. Unlike similar subjects, this course offers a realistic overview of the different steps necessary to carry out differential expression studies, functional annotation of sequences, or metagenomic profiling from sequencing data. All theoretical lessons are complemented with practical examples based on real data and applications in the industrial field.
On a more specific level, this course on Analysis and Visualisation of Genomic Data, which aims to enable professionals in the health sector or related sectors to learn how to handle and interpret data obtained through massive sequencing techniques, contributing to professional training in the health and agri-food sector, will be given.
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