Team Leader, Microbiome Informatics
Dr Rob Finn leads EMBL-EBI’s Microbiome Informatics team, which is responsible for the MGnify resource, which provides access to the metagenomics, metatranscriptomics and assembly analysis services. The functional and taxonomic profiles of these datasets, once made public, can be access by all via the MGnify website. The team is also responsible for the HMMER website, which enables fast proteins sequence similarity searches against a range of sequence and profile HMM databases. Rob also has a small research group that probes the functions of microbial 'dark matter'.
Rob joined EMBL-EBI from the Janelia Research Campus in the US, where he led a group that designed fast, web-based, interactive protein-sequence searches and annotations. Between 2001 and 2010, he was the project leader for Pfam at the Wellcome Trust Sanger Institute in the UK. Rob’s academic background is in microbiology and he holds a PhD in biochemistry from Imperial College, London.
rdf [at] ebi.ac.uk
ORCID iD: 0000-0001-8626-2148
Tel:+ 44 (0) 1223 492 679 / Fax:
The Microbiome Informatics Team develops the software and analysis pipelines that underpin the MGnify database. This team is also responsible for the HMMER webservers, which provide access to the HMMER software suite for performing sequence similarity searches. The Finn Team also includes the HGNC, headed by Elspeth Bruford, which is responsible for the assignment of gene symbols and names for protein coding genes, ncRNA genes and pseudogenes in human, and for gene naming in selected vertebrates as the VGNC.
Like all EMBL-EBI services, these data resources are freely available to all.
About our data services
Our services use complex mathematical models tailored for life-science research. For example, the HMMER3 algorithm offers fast detection of distantly related proteins and is available through our HMMER website infrastructure. We aim to simplify access to curated, complex data, and to maximise biological knowledge by extending annotation based on sequence similarity.
Understanding environmental samples
Our MGnify service enables researchers to submit sequence data and associated descriptive metadata about environmental samples to public nucleotide archives. Once deposited, our team helps ensure the data is functionally analysed (using an InterPro-based pipeline), taxonomically analysed and visualised via a web interface.
This graphic shows the workflow for our metagenomics analysis.
We participate in EMBL-EBI's Training Programme, offering courses in metagenomics and other approaches to sequence analysis.
We welcome new collaborations in all areas, and are particularly interested in working with people who have developed new tools for analysis, or who are working with metagenomics datasets generated with new sequencing technology.