These pages will update as the course progresses, consisting of relevant lecture notes, practical demonstrations (in R), exercise sheets and practical sessions. Welcome to the material for the first term of the module Advanced Statistical Modelling MATH3411 at Durham University. These are the course notes for the Machine Learning module of Durham University’s Masters of Data Science course. Read more → 19 CASA0005 Geographic Information Systems and Science by Andy MacLachlan and Adam Dennett This course will give students a detailed understanding of how omics technologies and data processing methods can be harnessed for pharmaceutical research applications. Fingally, we will survey key related advances in mass spectrometry-based proteomics that are enabling rapied, highly-multiplexed characterization of protein function in health and disease. Students will also learn how advanced functional genomics techniques can be applied to help develop new therapeutic strategies against major diseases. Students will learn how scientists sequence,assemble and analyze structure and function of genomes and explore methods for determining the heretibility of traits and diseases by studying the larger population. Students will then explore the key genomic technologies and computational approaches that are driving advances in prognostics, diagnostics and treatment.

This course will, through the lens of Pharmaceutical Science, provide an introduction and review of the general principles of genomics and molecular biology. These increases in our understanding of biology and human health can create breakthroughs in disease treatment and brings the prospect of personalized medicine closer to practical reality. Similar advances are ocurring for studying all the proteins within a cell (proteomics) and in our ability to manage and analyze all of the resulting data. Genetics and genomics are undergoing an unparalled revolution in terms of technical capabilities and their impact on human health.

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