Description

Overview:

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 has recently been introduced as a significant improvement in fully automated functional annotation. ARBA is a multiclass learning system which uses rule mining techniques to generate concise annotation models. ARBA employs a data exclusion set that censors data not suitable for computational annotation, and generates human-readable rules for each UniProt release.

We will also briefly touch on the mechanism UniProt has set up to enable researchers to run these automated annotation systems on their own protein datasets.

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

Subject:

Applied Science, Life Science

Level:

College / Upper Division, Graduate / Professional, Career / Technical

Material Type:

Lecture

Provider:

EMBL-EBI

Date Added:

01/14/2021