Teaching and assessment for Mathematical Biology BSc (Hons)

This module addresses the structures and biochemical properties of key biological molecules such as nucleic acids, lipids, carbohydrates and proteins. You will discover how enzymes work and look at their importance in the catalysis of biological reactions. The module also considers the origin of cells, and examines their main components.

You will continue to develop the research skills introduced during the previous semester. Undertaking a short independent research project will help you practice and extend your technical capabilities. You will gain understanding and practical experience of techniques such as PCR and agarose gel electrophoresis for DNA analysis.

The module addresses the cell cycle and cell replication, and the transfer of information from DNA to protein. It considers physiological systems and the specialisation and organisation of cells into the major organ systems. It develops an evolutionary perspective by considering the above processes and structures in diverse organisms.

Mathematics 1A is an introductory mathematics module.

It covers fundamental concepts such as algebra, calculus, and geometry.

The topics covered provide a solid foundation for more advanced studies. Skills covered include:

• learning to solve equations
• understand functions
• analyse graphs

Mathematics 1B builds on the foundational concepts introduced in Mathematics 1A. You will be introduced to matrices. You will learn about the use of vectors in 3D geometry, integral calculus, and basic differential equations. It ensures you are well-prepared for future studies in a maths or other numerate degree courses.

Starting university is a big step and we’re here to help you make the most of it.

No matter what subject you’re studying, there are important life and study skills that will help you succeed now and in the future.

You will learn about a key structure called a vector space.

Some of the simplest vector spaces are subsets of the 3-dimensional space in which we live. There are many other sets that share this structure.

You will learn more about solving differential equations.

Previously seen concepts such as linear independence, basis and null spaces are explored. This will be in the context of matrix algebra.

Concepts such as determinants and eigenvalues will be introduced.

Learn about partial derivatives and their properties.

Study integration of multi-variable functions including techniques such as change of variables.

You will learn to use data from a sample of a population to deduce information about the average properties of the whole population.

You will also learn how to use the software package RStudio to do calculations with data.

Master programming in Python and MATLAB through hands-on labs. Gain real skills used by scientists and engineers in industry every day. 

Now that you’ve settled into university life, it’s time to build on the foundations you set in your first year.

This second-year module is all about helping you take your development to the next level. This will cover this from a personal, academic, and professional perspective.

In this module you'll learn about objective experimentation in scientific research. This is a research method designed to minimise personal bias and subjective influences. You'll also explore how statistical techniques drive hypothesis-led enquiry and observation. 

This module explores an area of calculus involving derivatives of functions. Derivatives give the rate of change of a function. For example, speed is the rate of change of distance, while acceleration is the rate of change of speed. Differential equations are equations that involve functions and their derivatives.

This module explores vector calculus, which is an area of mathematics that combines 3D geometry with calculus. Vector calculus is concerned with differentiation and integration of functions in 3D space. It can apply to either scalar-valued functions or vector-valued functions.

Model real-world systems using numerical methods. Learn to solve equations, simulate dynamics, and code like a computational scientist.

Study how systems evolve over time. Learn how to model and analyse physical and biological systems using differential equations and qualitative methods.

You will independently study a specific mathematical topic. This will allow you to become a logical problem solver. These skills are highly sought after in a wide range of industries.

This module explores calculus, specifically to find derivatives of functions. Ordinary Differential Equations (ODEs) are equations involving derivative terms.

Very few ODEs can be solved exactly, so methods have been developed to find approximate solutions. In this module, you will learn the basic numerical methods for calculating these approximate solutions.

Mathematical Statistics is the application of probability theory to statistics. This is an important area, providing useful connections to other areas of Mathematics. Mathematical Statistics has applications across the sciences, business, government, and more. It is a core topic in the growing area of Data Science.