Biochemistry and Molecular Biosciences|Molecular Biology

EXPERIMENTAL BIOCHEMISTRY|PROTEIN STRUCTURE AND FUNCTION|PROTEIN PURIFICATION|MOLECULAR BIOLOGY

This module gives an introduction to techniques and approaches that are used to investigate biochemical problems, together with their underlying principles. It...

This module gives an introduction to techniques and approaches that are used to investigate biochemical problems, together with their underlying principles. It is also designed to give experience in practical work, calculations and reading scientific papers. Specific areas that are covered include pH, redox potentials and equilibrium; basic spectroscopy; amino acids, protein sequences and structures; mass spectrometry, NMR and X-ray methods; statistical methods; protein purification and assays; molecular biology methods; bioinformatics and homology modelling.

In addition to the lecture programme students take part in fortnightly tutorials in small groups of between 4 and 6 students. The tutorial programme will complement the lecture series and includes various problem solving exercises as well as reading current literature. In addition you will explore current research topics, give oral presentations, interview academics about their research and write essays for your tutor.

Illustrative lecture schedule (based on 2021/22 topics)

Introduction to the module

Statistics
pH, pKa, buffers and equilibrium

Free energy, redox potentials and pH electrodes
Spectrometry

Introduction to scientific computing

Introduction to Python
Applications of Molecular Biology
Omics

Purifying proteins
Introduction to Mass spectrometry

Methods in Mass spectrometry

Sequencing Using Mass Spectometry
Python problem solving

Methods for determining macromolecular structure and interactions

Bioinformatics

Homology Modelling

This module gives students a practical introduction to the construction of parametric and generative structures. The focus is on learning algorithmic...

This module gives students a practical introduction to the construction of parametric and generative structures. The focus is on learning algorithmic implementation in detail, with advanced programming techniques which directly relate to design problems and the build environment. At the same time, students are encouraged to think about how form and structure may adapt to its context, and in particular, how architecture may evolve through its occupation. This can to be achieved by methods such as generative design, optimisation, simulation and machine learning. The module runs as a series of type-along coding sessions in C# with tutorial support. Each session focuses on a specific technique, starting with generative techniques, before moving onto form generation, export of the results, and learning systems. The sessions are combined to showcase how particular design problems can be tackled via the use of bespoke computational solutions.