A unit of study with lectures, practicals and tutorials on the application of recombinant DNA technology and the genetic manipulation of prokaryotic and eukaryotic organisms. Lectures cover the applications of molecular genetics in biotechnology and consider the regulation, impact and implications of genetic engineering and genomics. Topics include biological sequence data and databases, comparative genomics, the cloning and expression of foreign genes in bacteria, yeast, animal and plant cells, novel human and animal therapeutics and vaccines, new diagnostic techniques for human and veterinary disease, and the genetic engineering of animals and plants. Practical work may include nucleic acid isolation and manipulation, gene cloning and PCR amplification, DNA sequencing and bioinformatics, immunological detection of proteins, and the genetic transformation and assay of plants.

Qualified students will participate in alternative components of BIOL3018 Gene Technology and Genomics. The content and nature of these components may vary from year to year.

Developmental genetics discusses major concepts and our current understanding of developmental biology with an emphasis on molecular genetics. The developmental genetics of animal and plant systems will be investigated, along with approaches used to determine gene function in relation to development of complex multicellular organisms. Topics include the features and resources for model organisms; the generation of mutants for forward and reverse genetics; the application of mutants to the study gene function and gene networks; spatial and temporal gene expression in pattern formation; quantitative trait loci analysis; utility of genome wide association studies; epigenetics in relation to inheritance; genome information in the study of human genetics. Reference will be made to the use of modern techniques in developmental biology such as transgenics, recombinant DNA technology, tissue-specific expression analysis. Various methods of genetic mapping will be covered. Practical work complements the theoretical aspects of the course and develops important skills in genetics.

Qualified students will participate in alternative components to BIOL3026 Developmental Genetics. The content and nature of these components may vary from year to year. Some assessment will be in an alternative format to components of BIOL3026.

How did the diversity of life arise? Why are there so many species? Why do animals and plants seem so well designed for their environments? How do we explain patterns of distribution across continents? These are some of the key questions that we will examine in this Unit. The Unit begins with a survey of the history of evolutionary thought, and the so-called 'new synthesis'; the melding of Darwinian evolution, systematics and genetics. The Unit will provide training in the principles, methods, and applications of evolutionary biology including systems of classification, the genetics of speciation and hybrid zones, molecular evolution, reconstruction of phylogenies, population genetics, historical interpretation of geographic distributions, evolution of sex, adaptation, human evolution, and selfish gene theory. Examples from a broad range of organisms and data sources will be used throughout the Unit. This Unit is valuable for students who intend to seek employment in areas such as biodiversity research, bioinformatics, ecology, taxonomy, biological conservation and teaching.

The content will be based on the standard unit BIOL3044 but qualified students will participate in alternative components at a more advanced level. How did the diversity of life arise? Why are there so many species? Why do animals and plants seem so well designed for their environments? How do we explain patterns of distribution across continents? These are some of the key questions that we will examine in this Unit. The Unit begins with a survey of the history of evolutionary thought, and the so-called 'new synthesis'; the melding of Darwinian evolution, systematics and genetics. The Unit will provide training in the principles, methods, and applications of evolutionary biology including systems of classification, the genetics of speciation and hybrid zones, molecular evolution, reconstruction of phylogenies, population genetics, historical interpretation of geographic distributions, evolution of sex, adaptation, human evolution, and selfish gene theory. Examples from a broad range of organisms and data sources will be used throughout the Unit. This Unit is valuable for students who intend to seek employment in areas such as biodiversity research, bioinformatics, ecology, taxonomy, biological conservation and teaching.

This unit of study will focus on the high throughput methods for the analysis of gene structure and function (genomics) and the analysis of proteins (proteomics), which are at the forefront of discovery in the biomedical sciences. The course will concentrate on the hierarchy of gene-protein-structure-function through an examination of modern technologies built on the concepts of genomics versus molecular biology, and proteomics versus biochemistry. Technologies to be examined include DNA sequencing, nucleic acid and protein microarrays, two-dimensional gel electrophoresis of proteins, uses of mass spectrometry for high throughput protein identification, isotope tagging for quantitative proteomics, high-performance liquid chromatography, high-throughput functional assays, affinity chromatography and modern methods for database analysis. Particular emphasis will be placed on how these technologies can provide insight into the molecular basis of changes in cellular function under both physiological and pathological conditions as well as how they can be applied to biotechnology for the discovery of biomarkers, diagnostics, and therapeutics. The practical component is designed to complement the lecture course and will provide students with experience in a wide range of techniques used in proteomics and genomics.

This unit of study will focus on the high throughput methods for the analysis of gene structure and function (genomics) and the analysis of proteins (proteomics) which are at the forefront of discovery in the biomedical sciences. The course will concentrate on the hierarchy of gene-protein-structure-function through an examination of modern technologies built on the concepts of genomics versus molecular biology, and proteomics versus biochemistry. Technologies to be examined include DNA sequencing, nucleic acid and protein microarrays, two-dimensional gel electrophoresis of proteins, uses of mass spectrometry for high throughput protein identification, isotope tagging for quantitative proteomics, high-performance liquid chromatography, high-throughput functional assays, affinity chromatography and modern methods for database analysis. Particular emphasis will be placed on how these technologies can provide insight into the molecular basis of changes in cellular function under both physiological and pathological conditions as well as how they can be applied to biotechnology for the discovery of biomarkers, diagnostics, and therapeutics. The practical component is designed to complement the lecture course and will provide students with experience in a wide range of techniques used in proteomics and genomics.
The lecture component of this unit of study is the same as BCHM3092. Qualified students will attend seminars/practical classes in which more sophisticated topics in proteomics and genomics will be covered.

In today's data-rich world more and more people from diverse fields are needing to perform statistical analyses and indeed more and more tools for doing so are becoming available; it is relatively easy to point and click and obtain some statistical analysis of your data. But how do you know if any particular analysis is indeed appropriate? Is there another procedure or workflow which would be more suitable? Is there such thing as a best possible approach in a given situation? All of these questions (and more) are addressed in this unit. You will study the foundational core of modern statistical inference, including classical and cutting-edge theory and methods of mathematical statistics with a particular focus on various notions of optimality. The first part of the unit covers various aspects of distribution theory which are necessary for the second part which deals with optimal procedures in estimation and testing. The framework of statistical decision theory is used to unify many of the concepts. You will apply the theory to various real-world problems using statistical software in laboratory sessions. By completing this unit you will develop the necessary skills to confidently choose the best statistical analysis to use in many situations.

This unit will introduce the fundamental concepts of analysis of data from both observational studies and experimental designs using classical linear methods, together with concepts of collection of data and design of experiments. You will first consider linear models and regression methods with diagnostics for checking appropriateness of models, looking briefly at robust regression methods. Then you will consider the design and analysis of experiments considering notions of replication, randomization and ideas of factorial designs. Throughout the course you will use the R statistical package to give analyses and graphical displays. This unit is essentially an Advanced version of STAT3012, with additional emphasis on the mathematical techniques underlying applied linear models together with proofs of distribution theory based on vector space methods.

Data Science is an emerging and inherently interdisciplinary field. A key set of skills in this area fall under the umbrella of Statistical Machine Learning methods. This unit presents the opportunity to bring together the concepts and skills you have learnt from a Statistics or Data Science major, and apply them to a joint project with NUTM3888 where Statistics and Data Science students will form teams with Nutrition students to solve a real world problem using Statistical Machine Learning methods. The unit will cover a wide breadth of cutting edge supervised and unsupervised learning methods will be covered including principal component analysis, multivariate tests, discrimination analysis, Gaussian graphical models, log-linear models, classification trees, k-nearest neighbors, k-means clustering, hierarchical clustering, and logistic regression. In this unit, you will continue to understand and explore disciplinary knowledge, while also meeting and collaborating through project-based learning; identifying and solving problems, analysing data and communicating your findings to a diverse audience. All such skills are highly valued by employers. This unit will foster the ability to work in an interdisciplinary team, and this is essential for both professional and research pathways in the future.

This unit is an Advanced version of STAT3014. There will be 3 lectures per week in common with STAT3014. The unit will have extra lectures focusing on multivariate distribution theory developing results for the multivariate normal, partial correlation, the Wishart distribution and Hotelling's T^2. There will also be more advanced tutorial and assessment work associated with this unit.

This unit will provide a comprehensive discussion of relevant OS issues and principles and describe how those principles are put into practice in real operating systems. The contents include internal structure of OS; several ways each major aspect (process scheduling, inter-process communication, memory management, device management, file systems) can be implemented; the performance impact of design choices; case studies of common OS (Linux, MS Windows NT, etc.).

This unit enables talents students with maturing IT knowledge to integrate various IT skills and techniques to carry out projects. These projects are largely research intensive.

This unit enables talents students with maturing IT knowledge to integrate various IT skills and techniques to carry out projects. These projects are largely research intensive.

This unit will provide students an opportunity to apply the knowledge and practice the skills acquired in the prerequisite and qualifying units, in the context of designing and building a substantial bioinformatics application. Working in groups, students will carry out the full range of activities including requirements capture, analysis and design, coding, testing and documentation.