KIUA2009 Use of AI and ML for studies in bio chemistry
- Course codeKIUA2009
- Number of credits10
- Teaching semester2026 Autumn
- Language of instructionNorwegian
- CampusHamar
- Required prerequisite knowledge
No special requirements
This course delves into the intersection of artificial intelligence (AI) and biochemistry. The course is designed for students with a background in AI and ML and provides an introduction to chemistry and biochemistry, enabling students to build a bridge between the two fields. AI and ML have enabled chemists and biochemists to analyse enormous volumes of data, optimise chemical processes and design new molecules and materials more quickly and more accurately than before. Among other things, AI is expected to have a major impact on how drugs and materials are discovered, developed and manufactured and could, for example, streamline the development of vaccines, as well as identification of possible adverse effects and production processes. The course covers the following topics:
- Atoms, molecules and the most important substance classes in organic chemistry
- Chemical bonds, molecular geometry and intermolecular forces
- Chemical reactions and chemical equilibrium
- Acids and bases
- Nucleic acids, replication, transcription, translation, amino acids and proteins
- The three-dimensional structure and function of proteins in the cell
- Enzymes, enzyme kinetics and regulation
- Structure of biological membranes
- Principles of energy metabolism in cells
- Computational chemistry and modelling
- The application of AI and ML in biochemistry
Learning Outcome
Upon passing the course, students will have achieved the following learning outcomes:
Students
- will have knowledge of basic concepts and theory in chemistry and biochemistry
- will have knowledge of calculations in connection with chemical reactions
- will have knowledge of the chemical composition of substances and the most important forms of chemical bonds and forces
- will have knowledge of the different substance classes in organic chemistry. This includes their structure and functional groups, isomerism, nomenclature and certain reactions
- will have knowledge of the structure and properties of important macromolecules
- will have knowledge of different reaction cycles and reaction pathways and will be able to explain their purpose
- will have knowledge of the structure and importance of enzymes as catalysts for biological reactions, as well as regulatory mechanisms for enzymes
- will have knowledge of deep learning algorithms and their applications in the analysis of protein structures, protein folding and functional genomics
- will have knowledge of molecular modelling and algorithms for homology modelling
Students
- will be able to use AI and ML as tools to perform calculations and solve complex tasks in biochemistry and adjacent fields
- will be able to perform pre-processing of data and use ML algorithms to predict protein structures and genomics analyses
- will be able to use AI to predict molecular interactions, identify potential drug candidates and optimise drug properties
- will be able to use techniques to integrate different data sources such as genomics, proteomics and metabolomics in order to gain comprehensive insights into complex biological systems
- will be able to use fundamental nomenclature, name and write formulas for simple compounds and describe the structure and properties of organic substances and will also have an overview of certain reactions
- will be able to convert units of measurement linked to mass, volume, temperature, amount of substance and concentration
- will be able to balance chemical reaction equations and perform calculations in connection with chemical reactions and chemical solutions
- will be familiar with selected key laboratory methods used in chemistry and biochemistry
Students
- will have knowledge of how AI and ML are expected to affect knowledge generation and working methods in biochemistry and adjacent fields
- will be able to use their AI and ML skills to solve challenges in chemistry and biochemistry
- will be able to exchange views and experiences with others
- will be able to communicate key subject matter in writing in Norwegian
- will be able to acquire new knowledge linked to the topics addressed on the course and seek and accept supervision
- will be able to discuss ethical issues relating to AI in biochemistry, including privacy and responsible research practices, as well as regulatory frameworks for AI-driven biotechnology
| Form of assessment | Grading scale | Grouping | Duration of assessment | Support materials | Proportion | Comment |
|---|---|---|---|---|---|---|
Written examination with invigilation | ECTS - A-F | Individual | 4 Hour(s) | 100 |
- 4-hour individual invigilated written examination
Performance is assessed using a grading scale from A-F, where E is the lowest passing grade.