Algorithms for Bioinformatics (COMP90014)

Technological advances in DNA sequencing, RNA sequencing and proteomics have provided a wealth of data from which biological insight can be obtained.  Refining this data is a non-trivial matter due to the increased input sizes seen in modern high-throughput bioinformatics.  This subject provides algorithmic strategies and data structures capable of meeting the challenge.  While focused on bioinformatic data, the concepts herein apply to big data analysis as a whole.

This subject covers key algorithms and data structures used in bioinformatics and assumes you have experience in programming. Strategies which frequently appear in modern software are explored so that bioinformatics tools may be appropriately selected, executed, and interpreted.  This exploration yields a toolkit from which new computational methods can be created. Indicative topics include sequence operations for comparison, alignment and indexing, graph data structures in the context of genome assembly, phylogenetics and network analysis, and both supervised and unsupervised machine learning within the fields of optimisation, dimensionality reduction, clustering and classification.

Intended learning outcomes

On completion of this subject the student is expected to be able to:

• Apply techniques to extract information from data and visualise results.
• Implement common bioinformatics algorithms, strategies, and data structures.
• Design and implement algorithms to solve new problems.
• Interpret outputs to diagnose, communicate, and remedy issues.
• Recognise which bioinformatics algorithms, data structures and strategies are best suited to a given task.
• Identify and mitigate the feasibility constraints imposed by computational complexity.

Generic skills

On completion of this subject, students should be able to demonstrate:

• Ability to decompose large problems into simple pieces.
• Creativity and mental flexibility.
• Improved coding literacy and software skills.
• Ability to set goals and measure success.