Molecular bioinformatics

The development of several high-throughput analytical approaches in molecular biology has revolutionized genomics. In particular, Next Generation Sequencing has wide applications in many functional genomics settings. This course will introduce a range of these applications, focusing on the nature of data generated, its strengths and limitations as well as computational and statistical approaches used to analyze genomic and transcriptomic datasets in various contexts.

At the end of the course, students will acquire:
- A knowledge of the scope of bioinformatics in genomics and functional genomics.
- A detailed appreciation of the nature of Next Generation Sequencing data from different platforms, their characteristics, advantages and weaknesses.
- An understanding of fundamental aspects of experimental design in genomics and transcriptomics.
- An understanding of data quality checking and filtering approaches.
- An appreciation of theoretical considerations underlying data analytical approaches in genomics and transcriptomics (genome assembly and annotation, variant detection, gene annotation, quantitative analysis of gene expression, analysis of small non-coding RNAs).
- The ability to critically interpret results of genome wide studies.
- Experience in the evaluation and synthesis of results of genomics experiments through the preparation and presentation of a scientific poster.