SLiMSuite Short Linear Motif discovery and analysis: Blog switchover

SLiMSuite Short Linear Motif discovery and analysis: Blog switchover: Posts and pages from the old SLiMSuite and SeqSuite blog have now been imported and this blog will take over as the main source of ongoing news, tips, documentation and updates.

SLiMSuite 2014-04-22 now available

SLiMSuite 2014-04-22 now available: A new download of SLiMSuite (release 2014-04-22) is now available. As well as fixing the gopher.py error, the download page and readme ha...

PPI-Net Poster: Computational prediction of short linear motifs integrating protein-protein interactions, sequence and structural data

Nico’s poster from the 3rd Protein-Protein Interaction Network (PPI-Net) Young Researchers Symposium is now available on F1000Posters:

Nicolas Palopoli & Richard J Edwards (2014) Computational prediction of short linear motifs integrating protein-protein interactions, sequence and structural data. F1000Posters 5: 407.

Abstract

Protein-protein interactions (PPI) between globular domains and Short Linear Motifs (SLiMs) play a crucial part in many biological processes. SLiMs are short stretches of 5 to 15 amino acids with high evolutionary plasticity that are usually found in disordered regions of proteins. Their role as ligands for molecular signalling, post-translational modifications and subcellular targeting has been increasingly studied over recent years, but experimental discovery of SLiMs remains a challenging task due to their small size and high degeneracy. As a consequence, computational tools for prediction and analysis of SLiMs are a valuable resource.

We have previously presented SLiMFinder, a motif discovery tool that applies a model of convergent evolution to estimate the statistical significance of over-represented motifs. In this project we aim to improve motif discovery by integrating SLiMFinder with methods that predict new domain-motif interactions directly from structural features in high-resolution 3D data. To this end we have developed “Query” SLiMFinder (QSLiMFinder) which uses knowledge of the interaction interface to constrain the motif search space and thereby increase search sensitivity. Using putative SLiM-carrying regions extracted from protein structures as queries and targeting data from public protein-protein interaction databases, we applied QSLiMFinder to find over-represented recurring sequence patterns from proteins that all share a common interaction partner.

Benchmarking of QSLiMFinder shows that specific domain-motif interaction data help in finding novel instances of known motifs or entire de novo SLiMs, improving over results returned by PPI data alone. SLiM discovery capitalizes from the availability of experimentally identified PPIs with high-quality predictions of the interacting sites. The methods developed here help to enhance annotation in public databases of SLiMs and could be used to mine new PPI data as it becomes available, adding molecular detail to interactome networks.

SLiMSuite & SeqSuite: New downloads and fixed webpages

SLiMSuite & SeqSuite: open-source bioinformatics in Python: New downloads and fixed webpages: New releases of SeqSuite and SLiMSuite are now available. The webpages have now hopefully been fixed too, including the broken Manual link...

Postdoc opportunity in Short Linear Motif discovery!

As part of the move to UNSW, a 10 month computational postdoc position is available in the lab. The position is not attached to a specific grant and thus the research focus of the position is flexible and open for negotiation. It will, however, be something related to the lab’s primary research focus of computational Short Linear Motif (SLiM) discovery.

Possible projects include (but are not limited to): molecular mimicry by viral or bacterial pathogens; the role of SLiMs in cancer; interrogating protein-protein interaction networks to predict SLiM function; SLiM prediction database/visualisation development. For more on the research of the lab, please visit my old University of Southampton and/or new UNSW pages or email for more information.

Short-listing will (probably!) begin on 1/12/13 but applications are welcome until the position is filled. To apply, or find out more, please email a copy of your CV and your research interests. Candidate should have good computational skills. Start date is flexible but likely to be around January 2014.

SLiM Pickings: mining structural and sequence data for the prediction of short linear protein interaction motifs

Less than a week after starting at UNSW, I was lucky enough to present the work of the lab on Short Linear Motif (SLiM) discovery at the third annual Sydney Bioinformatics Research Symposium, which was held on Friday 8th November at the Garvan Institute. It was a great day, organised by the Australian Bioinformatics Network (ABN) for bioinformaticians and bioscientists in the Sydney region, and I was pleased to see so much exciting stuff going on in the Sydney area and beyond.

Now at the University of New South Wales!

As of Monday 4th November 2013, Rich is a Senior Lecturer in Bioinformatics in the School of Biotechnology and Biomolecular Sciences (BABS) at the University of New South Wales (UNSW) in Sydney, Australia.

The new primary contact details for the lab are:

Room 263B Level 2 Biological Sciences Building
The University of New South Wales
SYDNEY NSW 2052
Australia
email: richard.edwards@unsw.edu.au
web: http://www.babs.unsw.edu.au/staff_academic/dr-richard-edwards

Due to grant restrictions and collaborations, the rest of the lab are staying in Southampton. For now..!