UniProt is a high quality, comprehensive protein resource in which the core activity is the expert review and annotation of proteins where the function has been experimentally investigated. At the same time, the UniProt database contains large numbers of proteins which are predicted to exist from gene models, but which do not have associated experimental evidence indicating their function. UniProt commits significant resources to developing computational methods for functional annotation of these predicted proteins based on the data in entries that have gone through the expert review process.

We will describe the two main automated annotation systems currently in use. First, UniRule, which is an established UniProt system in which curators manually develop rules for annotation. Second, ARBA (Association-Rule-Based Annotator), which is a multi-class learning system which uses rule mining techniques to generate concise annotation models. ARBA employs a data exclusion algorithm that censors data not suitable for computational annotation, and generates human-readable rules for each UniProt release.

We will also introduce UniFIRE, an open source software that enables researchers to annotate their own protein dataset by using the above mentioned annotation systems. In order to provide an easy and straightforward way to download and set up this tool we have containerised UniFIRE together with all its dependencies and the latest set of UniRule and ARBA rules. In this webinar, we will show how to create functional predictions for protein sequences by using this container image.

Who is this course for?

This webinar is for scientists and bioinformaticians with an interest in functional annotation of protein sequences.

Outcomes

By the end of the webinar you will be able to:

• Recall the role of UniProt's two main automated annotation systems
• Describe how UniRule and ARBA work
• Get started using these automated annotation systems

DOI: 10.6019/TOL.UniProtAnnotation-w.2021.00001.1

This webinar took place on 3rd February 2022. Please click the 'Watch video' button to view the recording.

This webinar took place previously on 14th January 2021. View the recording and slides.