BI3ART1: Advanced Research Techniques

Module code: BI3ART1

Module provider: School of Biological Sciences

Credits: 20

Level: 6

When you’ll be taught: Semester 1

Module convenor: Dr Connor Sharp , email: c.sharp@reading.ac.uk

Module co-convenor: Professor Kimberly Watson, email: k.a.watson@reading.ac.uk

Pre-requisite module(s):

Co-requisite module(s):

Pre-requisite or Co-requisite module(s):

Module(s) excluded:

Placement information: NA

Academic year: 2025/6

Available to visiting students: No

Talis reading list: Yes

Last updated: 3 April 2025

Overview

Module aims and purpose

Advances in technology have transformed the life sciences. New tools allow us to examine the details of protein folding, structure, and function with increasing precision. Although the first bacterial genome was sequenced only in 1995, research now involves analysing thousands of genomes. Modern life science research combines multiple techniques and data types to study biology on various scales, from changes in entire populations to the atomic structure of individual proteins. 

In this module, you will learn the state-of-the-art techniques and tools used in modern life science research and how they can be combined to answer real research questions. This module will provide you with an understanding of modern techniques in genomics, transcriptomics, proteomics, and metabolomics. You will learn the strengths and limitations of these techniques, how to interpret the diverse data types produced in modern biology, and how to combine various techniques to address real research questions. 

Module learning outcomes

By the end of the module, it is expected that students will be able to: 

1. Describe the different types of data encountered in modern biological research and the tools needed for its analysis 
2. Use web-based tools to retrieve, manipulate, analyse and interpret biological data. 
3. Explain how researchers integrate different techniques and data to answer questions in biology and evaluate the strengths and weaknesses of current, state-of-the-art approaches. 

Module content

Lecture material includes the following topics:

• The types and scales of data encountered in biology research and the need for tools to analyse data
• The interplay between computational and experimental biology.

Genomics

• Sequencing genomes: Sequencing methods (Sanger, NGS, Nanopore) and assembling short reads
• Sequencing as a tool: ChIP-Seq, Tn-Seq/TraDIS,
• Functional annotation of genomes: Finding genes, motifs and domains, functional prediction, identifying AMR genes and virulence factors, and structure prediction
• Biological data resources: Online databases and tools for analysing genomes
• Sequence alignment and phylogenetics: Homology, sequence evolution, phylogenetics, sequencing populations, Genome-wide association studies, bacterial pangenomes and comparative genomics
• Metagenomics: Profiling microbial community composition with 16S/18S, metagenomic assembled genomes, sequencing the human microbiome

Transcriptomics

• Gene regulation: DNA motifs, transcription factor binding sites and regulons
• Principles of measuring transcription: RNAseq, normalization, differential analysis
• Advances in transcriptomics: singles cell, meta- and spatial transcriptomics

Proteomics and metabolomics

• Quantifying changes in protein abundance
• Modelling metabolic pathways and systems

Protein Structure and Function

• Protein expression and engineering
• Protein structure and folds
• Protein design
• Protein structure tools – X-ray crystallography and Cryo-Electron Microscopy 
• Artificial intelligence in studying proteins

Practical classes include:

• Running common bioinformatics s