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DTSTAMP:20260829T170855Z
UID:9353ab13-4ad8-4963-b404-4c8e879f5554
DTSTART:20220203T150000Z
DTEND:20220203T160000Z
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 annotatio
 n systems currently in use. First\, UniRule\, which is an established UniP
 rot system in which curators manually develop rules for annotation. Second
 \, ARBA (Association-Rule-Based Annotator)\, which is a multi-class learni
 ng system which uses rule mining techniques to generate concise annotation
  models. ARBA employs a data exclusion algorithm that censors data not sui
 table for computational annotation\, and generates human-readable rules fo
 r each UniProt release.\n\nWe will also introduce UniFIRE\, an open source
  software that enables researchers to annotate their own protein dataset b
 y using the above mentioned annotation systems. In order to provide an eas
 y and straightforward way to download and set up this tool we have contain
 erised UniFIRE together with all its dependencies and the latest set of Un
 iRule and ARBA rules. In this webinar\, we will show how to create functio
 nal predictions for protein sequences by using this container image.\n\n
SUMMARY:Automated annotation in UniProt
URL;VALUE=URI:https://www.ebi.ac.uk/training/events/automated-annotation-un
 iprot
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