Cheminformatics

Learning Outcomes

Subject Specific Intellectual and Research Skills

Having successfully completed this module you will be able to:

• How to make inference using chemical data
• Understanding algorithmic approaches to how molecular representations can be generated

Transferable and Generic Skills

Having successfully completed this module you will be able to:

• Data analysis and pattern recognition

Knowledge and Understanding

Having successfully completed this module, you will be able to demonstrate knowledge and understanding of:

• How molecules can be represented
• How advanced data analysis and computational models are applied to analysing chemical data

Basic chemistry - understanding basic human readable representations of molecules

Representations - Smiles, De Morgans Algorithm, sdf, mol, fingerprints,

Similarity methods - clustering, Ullmann algorithm,

Graph algorithms - smallest set of smallest rings

Data - what data is available, how to explore it

Property and reactivity prediction - QSAR including regression, basic ML, GBMs, GNNs, Coley et al,

Lectures, tutorials labs.

Use of VLE to provide continuous formative assessment in the form of quizzes. Labs assessed as formative assessment.

The final coursework will use an aspect of each lab.

Lectures will provide background theoretical information, with additional readings and videos supplied via VLE.

Summative

This is how we’ll formally assess what you have learned in this module.