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Module Summary

This module will focus on the computational biology aspects of personalised and genomic medicine. You will learn how bioinformatics and genomics have shaped personalised medicine; the bioinformatics challenges for personalised medicine and how to use computational biology and genomic technologies as tools for the future of personalised medicine. This will include algorithms, bioinformatic pipelines and databases to understand the inter-individual genetic variation underlying disease. The functional annotation of genetic variants and their contribution to both common and rare diseases will be discussed, as well as their interpretation using multiple sources of functional information (transcriptomics, proteomics, metabolomics and others). New genomic technologies of application to personalised medicine and their analysis will also be discussed.Ìý

Learning outcomes and objectives

This module will give the student a good understanding of how the current practices of bioinformatics and genomics are shaping personalised medicine. The main aim of this module is for students to understand the bioinformatics challenges for personalised medicine and to provide the computational knowledge to interpret human genetic variation in common and rare human disease as well as the technologies underlying personalised medicine.

Who is this module for?

This is a core module for the MSc Personalised Medicine and Novel Therapies programme

Teaching and Learning methods

The module will make use of online learning practices as well as multi-tutor led computer practical sessions from leading computational and genomic biologists at GOS ICH. This module will be conducted in a dedicated computer cluster and students will learn how to conduct and complete a case study (from conception to analysis) and understand the importance of computational biology in shaping the future of science and medicine through a balanced mixture of lectures, case studies, tutorials, problem solving and small group working.Ìý

Assessment

The assessment will consist in a combination of theoretical and practical short questions, based on concepts discussed through these sessions. You will be allowed to bring notes and access databases online.

Selected reading list

1. Abril JF and Castellano S. Genome Annotation. In Encyclopedia of Bioinformatics Bruno Gaeta (Ed.) Elsevier (2018)Ìý

2. Hindorff LA, Bonham VL, Brody LC, Ginoza MEC, Hutter CM, Manolio TA and Green ED. Prioritizing diversity in human genomics research. Nat Rev Genet. (2018)Ìý

3. Torkamani A, Wineinger NE and Topol EJ. The personal and clinical utility of polygenic risk scores. Nat Rev Genet. (2018)Ìý

4. Wright CF, FitzPatrick DR and Firth HV. Paediatric genomics: diagnosing rare disease in children. Nat Rev Genet. (2018)Ìý

5. Karczewski KJ and Snyder MP. Integrative omics for health and disease. Nat Rev Genet. (2018)Ìý

6. Zhang J, Wang W, Huang J, Wang X, Zeng Y. How far is single cell sequencing from clinical application? Clin Transl Med. (2020)Ìý

7. Kim, J., Koo, BK. & Knoblich, J.A. Human organoids: model systems for human biology and medicine. Nat Rev Mol Cell Biol 21, 571–584 (2020)Ìý

8. Mitsuhashi, S., Matsumoto, N. Long-read sequencing for rare human genetic diseases. J Hum Genet 65, 11–19 (2020)Ìý

9. Rood, J., Maartens A., Hupalowska A., Teichmann S., Regev A. Impact of the Human Cell Atlas on Medicine. Nature Medicine 28, 2486-2496 (2022).Ìý