UQ SCIE
Bioinformatics is about applying computational and mathematical thinking to the biological sciences, changing how we approach scientific problems, and increasing the scale and complexity of the problems we are able to solve.
Genome sequencing projects, complementary high-throughput and combinatorial biotechnologies generate data at a rate far beyond the reach of our ability to inspect and synthesize knowledge from it. The opportunities for computationally interpreting this data—to convert patterns into meaningful biology—are ripe. Moreover, current tools are quickly outdated, requiring new bioinformatics methods to be developed.
The course covers the principles and methods that let us search and compare DNA, RNA and proteins, cast as biological sequences. The course explains why they can give us answers to fundamental biological questions important to fields such as cell biology, biochemistry and medical science.
The course covers technologies and methods for analysing the expression, structure and function of DNA, RNA and proteins, and for understanding the relationship between species. We discuss important public databases that provide details of biological systems and components. Throughout, the course instils and nurtures computational thinking and skills to support the analysis of large-scale data sets, using a problem-based learning approach. We refer to practical problems where such thinking pays dividend and highlight pitfalls along the way.
Industries searching for bioinformatics and computational biology graduates include: health, agriculture, biotechnology, pharmaceuticals and environmental management. Graduates equipped with bioinformatic skills are particularly sought after in the areas of drug design and patent management, gene therapy, crops and livestock breeding (and farming), aquaculture and environmental management for their ability to translate biological data into practical optimised solutions.
• M. Zvelebil and J. O. Baum, Understanding Bioinformatics, ISBN 0-8153-4024-9. Garland Science, 2007. (UQ Library code: QH324.2.Z84 2008)
• S. T. Kelly and D. Didulo, Computational Biology: A Hypertextbook, Print ISBN 9781683670025, Ebook ISBN 9781683670032. ASM Press, Washington DC, 2018. (UQ Library code: QH324.2 .K45 2018)
Each practical have a html file that include the informative problem description and quiz questions.
My working can be viewed by running jupyter files in each practical's folder:
jupyter prac_file_name.jpynb- Gain basic competency in bioinformatics, including a broad basic understanding of molecular biology and biochemistry, and attainment of practical skills and analytical thinking to solve scientific problems using computing.
- Understand the scope of bioinformatics—the application of computational and mathematical thinking to the biological sciences. This understanding is approached both as a bioinformatics “user” and bioinformatics “developer”.
- Be aware of representative ideas in the area of bioinformatics—how different ideas in bioinformatics can be used to approach scientific problems, and what problems we can feasibly solve.
- Consolidate a basic knowledge in biology in order to understand the nature of a range of bioinformatics problems.
- Develop an awareness of, and expertise within, different types of bioinformatics problems and recognize the appropriate level of abstraction of each problem.
- Identify and describe the potential, scale, scope and limitations on computational approaches and biological data sets.
- Conceptualise and utilise the iterative design process of observed biology and computational approach as an effective model for understanding biology.