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DTSTAMP:20260708T120911Z
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DTSTART:20260312T090000Z
DTEND:20260312T170000Z
DESCRIPTION:UniProt is a high quality\, comprehensive protein resource in w
 hich the core activity is the expert review and annotation of proteins whe
 re the function has been experimentally investigated. At the same time\, t
 he 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 pr
 edicted proteins based on the data in entries that have gone through the e
 xpert review process.   \n  \nWe will describe the two main automated ann
 otation systems currently in use. First\, UniRule\, which is an establishe
 d 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 anno
 tation models. ARBA employs a data exclusion algorithm that censors data n
 ot suitable for computational annotation\, and generates human-readable ru
 les for each UniProt release. As part of our interest in engaging with the
  machine learning community\, we will also introduce the contribution of P
 rotNLM (Protein Natural Language Model)\, from Google Research\, which ann
 otates proteins which have "uncharacterised" names.   \n  \nWe will also 
 introduce UniFIRE\, an open source software that enables researchers to an
 notate their own protein dataset by using the above mentioned annotation s
 ystems. In order to provide an easy and straightforward way to download an
 d set up this tool we have containerised UniFIRE together with all its dep
 endencies 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.
LOCATION:\, 
SUMMARY:Automatic annotation systems in UniProt
URL;VALUE=URI:https://www.ebi.ac.uk/training/events/automatic-annotation-sy
 stems-uniprot
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