Recent news

Neurological Gene Annotation Initiative Newsletter April 2017

The UCL Neurological Gene Annotation Newsletter is now available at: The Neurological Gene Ontology Annotation Initiative represents a collaboration between University College London, the European Bioinformatics Institute (EBI), and University of Manchester, funded by Alzheimer's Research UK (grants ARUK-NSG2016-13 and ARUK-NAS2017A-1).

Cardiovascular Gene Annotation Newsletter February 2017

The UCL cardiovascular gene annotation newsletter is now available at and summarises the aims of the new Alzheimer's project, suggests how to create a microRNA:mRNA network overlaid with GO terms @UCLGene

The UCL neurological gene annotation newsletter is now available at

We welcome Barbara Kramarz (nee Czub), who is moving from the Cardiovascular annotation team, and describe our continued focus on genes for which there is genetic evidence of a role in Parkinson’s.

Cardiovascular Gene Annotation Newsletter August 2016

The UCL cardiovascular gene annotation newsletter is now available at We describe our progress annotating miRs with GO, our recent bioinformatics training workshop and provide some information about our overseas visitor, Wafa Omer

Cardiovascular Gene Annotation Newsletter May 2016

The UCL cardiovascular gene annotation newsletter is now available at This newsletter highlights annotation of the miR-17~92 cluster, our RNA paper and our forthcoming 2-day bioinformatic resources workshop.

Paper on extending GO in the context of extracellular RNA and vesicle communication

To address the lack of standard terminology to describe extracellular RNA data and metadata, a team of several academic societies collaborated with the GO Consortium to extend the Gene Ontology with subcellular structure concepts relevant to the exRNA domain. As a result, exRNA data and metadata will be more easily annotated and queried because it will


The GO has historically provided access to annotations in a format called GAF (Gene Association Format). This format allows detailed representation of evidence and metadata for a GO term association, but has historically been limited in how well it can express important details of the cellular biology being described.

This has lead to a number of incremental improvements, while retaining compatibility, ultimately leading to the new expressive LEGO format.