Evolution is the biological process that has generated the biodiversity on this planet. It explains the common ancestry of all life on earth, why all organisms use the same genetic code, and why major life forms are constrained to a relatively small number of basic body plans such as four limbs in tetrapods. Thus, the principles of evolution and population genetics underpin all biology, including ecology, medicine and agriculture. For example, it is only because rats and humans share an evolutionary past that we can use rats as models for human medical research. In this unit, you will explore the mechanisms that generate evolutionary change at both contemporary and ancient scales. You will learn how to use DNA sequences to reconstruct the relationships among organisms and to estimate evolutionary timescales. Evolution is an ongoing process, so you will use genetic techniques to discover whether populations are divided into subpopulations. By completing this unit, you will develop skills in genomics, phylogenetic analysis, population genetics and conservation genetics. You will learn about fundamental aspects of evolution such as adaptation, sexual selection, and the origins of life. You will gain general skills in computer literacy, data management and statistical genetics.

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.

The advent of multicellularity represents one of life's great transitions in complexity, ultimately paving the way to the evolution of complex organisms such as humans. This unit focuses on how such complex multicellular systems are constructed using both animal and plant systems in a comparative way that reveals common strategies and striking contrasts. The course will cover the multidisciplinary nature of approaches used, including classical embryology, biochemistry, genetics, transcriptomics, live-imaging, cell biology, physiology and computer simulation. Topics will include fundamental concepts, morphogens, establishing body axes, cell polarity, differentiation and commitment, evolution in the context of development, mechanics and morphogenesis with examples from model systems, stem cells and cancer. Practical work complements the theoretical aspects of the course and develops important skills in developmental biology.

Qualified students will participate in alternative components to BIOL3026 Developmental Biology. 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.

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.

The sequencing of the human genome was a landmark achievement in science and medicine, marking the 'Age of Genomics'. Now we can access the blueprints for life, but need to uncover how those blueprints work, allowing organisms to respond to internal and external environmental changes, and how we can utilise this plethora of DNA sequence information to improve human and planetary health. This unit will investigate the function of the genome by examining the proteome, metabolome and beyond. You will investigate links between the central dogma of molecular biology and the complexities of living genomes - from modifications that massively increase diversity to the dynamic metabolome. You will explore fundamental cellular processes and discover how they are shaped by the proteome via gene expression, post-translational modification and protein complex formation. These processes will be examined in the context of human health and cardiovascular and metabolic disorders (e. g. type 2 diabetes) to demonstrate how global approaches can define, diagnose and help develop treatments for disease. You will practice methods employed in the post-genome era, including the 'Multi-omics' approaches that provide a global view of living systems, and discover how they are applied to solve problems in biology, biomedicine and agriculture. By the end of the unit students will understand why global 'omics approaches are needed in the post-genome era and know how best to apply such tools to given biological and biomedical problems.

The sequencing of the human genome was a landmark achievement in science and medicine, marking the 'Age of Genomics'. Now we can access the blueprints for life, but need to uncover how those blueprints work, allowing organisms to respond to internal and external environmental changes, and how we can utilise this plethora of DNA sequence information to improve human and planetary health. This unit will investigate the function of the genome by examining the proteome, metabolome and beyond. You will investigate links between the central dogma of molecular biology and the complexities of living genomes - from modifications that massively increase diversity to the dynamic metabolome. You will explore fundamental cellular processes and discover how they are shaped by the proteome via gene expression, post-translational modification and protein complex formation. These processes will be examined in the context of human health and cardiovascular and metabolic disorders (e. g. type 2 diabetes) to demonstrate how global approaches can define, diagnose and help develop treatments for disease. You will practice methods employed in the post-genome era, including the 'Multi-omics' approaches that provide a global view of living systems, and discover how they are applied to solve problems in biology, biomedicine and agriculture. Beyond the Genome (Advanced) has the same overall structure as BCMB3004 but focuses on a more advanced level of practical work, data analysis and interpretation, using cutting-edge technologies. By the end of the unit students will understand why global 'omics approaches are needed in the post-genome era and know how best to apply such tools to given biological and biomedical problems.

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.