Fundamentals of bio-entrepreneurship; business and financial planning; routes to market: intellectual property; the scientific method and applications to society, experimental design, philosophy of science, inter-disciplinary research
Mass spectrometry forms the basis of many analytical techniques in the biological and life sciences. This module will give students a foundation in the theory of mass spectrometry and how it can be applied to the study of biological systems. This will include the fundamentals of mass spectrometry instrumentation, ionisation, and chromatography and explore applications in targeted analysis, proteomics, and metabolomics. The majority of the course material will be broadly applicable across the biological sciences, but some course topics and assessments will include material, such as case studies and literature critiques, that are directly related to their postgraduate degree programme.
Bioinformatics Data sources & Sequence analysis: Databases and data availability. Analysis of DNA and Protein sequences – sequence searching methods, multiple sequence alignments, residue conservation, Protein domains and families. Protein Bioinformatics Methods: Protein structure and function prediction. Prediction of binding sites/interfaces with small ligands and with other proteins (e.g., Bioinformatics analyses using protein data, AutoDock prediction of how small molecules, e.g. substrates or drug candidates, bind to a receptor of known 3D structure). Genomics: An introduction to the analysis of genomic data, primarily focussing on the data available from genome, exome and transcriptome sequencing – and how it can be used to study genetic variants and compare genomes (i.e., comparative and functional genomics), RNAseq data analysis. This will be accomplished using Galaxy (an open source, web-based platform for data intensive biomedical research) and Cytoscape an open source software platform for visualizing complex patterns in data. Understand systems level approaches for genomic data analyses – e.g., Gene Ontology analysis, Over- representation analysis, Biological Pathway analysis, Co-expression network analysis, Gene Set enrichment analysis etc – and develop proficiency in tools such as Gorilla, Revigo, iPathway Guide, ToppFunn and Webgestalt. Environmental DNA (eDNA) monitoring-e.g., bioinformatics tools utilized to analyze eDNA samples, aiding in biodiversity assessments and ecological monitoring. Application of artificial intelligence (AI) in the field of food authenticity – exploration of software tools that can detect adulteration, mislabeling, and contamination with high accuracy, offering a robust solution to traditional methods. The objective of this module is to equip the next generation of biological scientists with an appropriate working knowledge of bioinformatics methods and concepts such that they can understand and critically evaluate the computational methods routinely used in high throughput analytical technologies (DNA sequencing/Mass Spectrometry). As most of the students will not have expertise in command line manipulation and programming the application of these bioinformatics methods will be achieved using GALAXY and Cytoscape which provide intuitive, user-friendly graphical interfaces. The analytical pipelines will be illustrated with biological or biomedical examples from peer-reviewed scientific literature. The module will equip the students with sufficient understanding of the subject to effectively communicate and collaborate with specialist bioinformaticians in managing, modelling, analysing and extracting knowledge from big biological data. It will provide a solid foundation for those wishing to go on to Ph.D. level study in bioinformatics, systems biology and related fields.
| QS 综合 | 院校 | 学制 | 学费 |
|---|---|---|---|
| 第 82 位 | 谢菲尔德大学The University of Sheffield | 1年 | 36055英镑/年 |