Two days before the main ISMB 2016 conference in Florida, the Network Biology Special Interests Group (NetBioSIG) meeting will take place. It is a great opportunity to meet up with experts in the field, so I hope to see you there. This years NetBioSIG will have four keynotes given by Olga Troyanskaya, Franca Fraternali, Nataša Pržulj, and yours sincerely.
There is of course also a chance for you to present your own work. However, please note that the abstract submission deadline is Friday, April 29. Please see the NetBioSIG website for more details.
At Intomics A/S, we are looking for a web developer to develop bioinformatics solutions for visualization and exploration of biomedical big data.
Note that the application deadline is April 1, three weeks from now. For further details, please read the job advert below the fold.
In collaboration with Jan Gorodkin at the Center for non-coding RNA in Technology and Health at University of Copenhagen, I will be starting up a project on cross-species network and pathway analysis of animal disease models. We have secured funding for the project and are now searching for the right person to fill a postdoc position.
The application deadline is February 27, 2016. For further details, including how to apply, please refer to the official job announcement.
The STRING database of known and predicted protein–protein interactions is a heavily used resource by bioinformaticians and non-bioinformaticians alike. The former generally use STRING via its web interface, whereas the latter typically download the complete network and analyze it locally. However, we lacked a good way for non-bioinformaticians to work with networks that are just too large for the web interface. A typical example of this would be users, who wish to visualize the results of a proteomics or transcriptomics study as a STRING network.
To address this, I have worked with John “Scooter” Morris to develop a new Cytoscape app for STRING. The app allows you to quickly retrieve much larger networks than is possible via the web interface and gives you the powerful layout and analysis features of Cytoscape. At the same time, it retains the “glass ball” look that many people associate with a STRING network (shown here with a small example network):
When retrieving network, the app also includes node attributes from the COMPARTMENTS and TISSUES databases. This allows users to easily, for example, color the nodes based on the confidence with which each protein is localized to a certain cellular compartment or expressed in a certain tissue. The app also includes node attributes for drug targets classification of human proteins, which are obtained from the Pharos web resource. Finally, since it is Cytoscape, you can obviously import your own attributes table.
Although it is not yet feature complete, version 0.9 of the app is already available from the Cytoscape App Store under the name stringApp. Please note that it requires Cytoscape 3.3 to work.
About a month ago, I received an email from an otherwise happy user of COMPARTMENTS, who wished there was a way to return to the search results after having clicked a protein. I was just about the send her an email explaining how the lack of “back” button functionality was an inherent drawback of using AJAX, when I thought that it would be wise to do a quick Google search first.
The result was a healthy serving of humble pie from Stack Overflow. It turns out that you can make it work fairly easily by using the
So there you have it. AJAX is no excuse for the “back” button not working as it should.
Having just downloaded the new Medline baseline, it is time to update the BuzzCloud and see what has changed since last year:
Comparing the cloud to that of last year, one new notable term is medical proteomics, which I believe is indeed something we will see become reality over the next years. The term precision medicine keeps going strong and has spawned a related term, namely precision oncology. Also related to this topic, wearable electronics receive increasing attention in the biomedical literature.
June 2016 will likely be a highly productive month for people in my group, since I will not be there much to disturb them. Specifically, I will be involved in running two week-long EMBO practical courses.
One was announced on this blog just two days ago. The other is the also long-running course “Computational biology: Genomes to systems”, which this year will take place on June 19–23 at the European Molecular Biology Laboratory in Heidelberg, Germany. The course will cover a wide range of advanced computational biology topics, including protein networks (taught by STRING collaborator Christian von Mering) and biomedical text mining (taught by me).
Please note that the application deadline is less than a month away, namely on January 31.
More details can be found on .
Later this year, I will once again be one of the teachers on the long-running EMBO practical course “Computational analysis of protein-protein interactions: Sequences, networks and diseases”. The 2016 version of the course will be taking place on May 30 – June 4 in Budapest, Hungary, and the application deadline is February 1.
For more details see the course website or the poster below.
At Intomics A/S, we are looking for a text-mining expert to perform contract research and develop taylor-made solutions. The job will primarily involve solving text-mining problems for clients in the pharmaceutical industry.
Note that the application deadline is January 15, just over two weeks from now. For further details, please read the job advert below the fold.
As mentioned in the last entry, 2015 has been a year of publishing web resources for my group. The COMPARTMENTS and DISEASES databases have yet another sister resource, namely TISSUES.
This web resource allows users to easily obtain a color-coded schematic of the tissue expression of a protein of interest, providing an at-a-glance overview of evidence from database annotations, from proteomics and transcriptomics studies as well as from automatic text mining of the scientific literature:
Whereas the resource integrates all of the above-mentioned types of evidence, the focus in this work was primarily on combining data from systematic tissue expression atlases, produced using a variety of different high-throughput assays. This required extensive work on mapping, scoring, and benchmarking the different datasets to put them on a common confidence scale. The scientific results and details of all those analyses can be found in the article “Comprehensive comparison of large-scale tissue expression datasets”.