Tag Archives: interactions

Cytoscape releases v2.7

Just got an announcement from the Cytoscape mailing list.  One of my favorite tutorials* that we’ve developed was Cytoscape–It was an interesting challenge for us because most of our focus has been tools with web interfaces and we had to address installation with this one.  But it was such a nice tool with great features that I really simply enjoyed working with it.

Anyway, here’s what’s new:

Hi everyone,

The Cytoscape team is proud to announce the release of Cytoscape 2.7!  This release includes some exciting new features:

* Nested Networks: A node may now have a reference to another Network, which allows us to capture the relationships between networks in networks themselves.

* CyCommandHandlers: Addition of a mechanism to the core to provide inter-plugin communication.

* New Edge Types: Several new edge types between solid and dashed have been added.

* Newlines and list editing in attribute browser: The attribute browser has been updated to allow newline characters to be added by pressing the “Enter” key. List editing is now also enabled.

* Automatic label wrap: A new visual property has been added that sets the width of a label. Any label extending beyond this width will be automatically wrapped.

* Arrow color optionally locked to edge color: Arrow color may now be bound to the edge color by checking a box in the Dependencies pane of the Default Appearance Browser in the VizMapper, which avoids the necessity of creating separate-yet-identical mappings for edge, source, and target arrows.

* BioPAX Level 3 support.

You can get the release here: http://cytoscape.org

Please let us know if you have any questions!

The Cytoscape Team

*The Cytoscape tutorial we have in part of our subscription package. For freely available sponsored tutorials you can click here.

Reactome wants to hear from you

reactome_rReactome has long been one of our favorite resources for looking at pathways and interactions.  The data quality is very high, and there are some very fun tools to use.   In fact, they were one of the earliest tutorials we did years back (but of course we have updated since).

If you aren’t already familiar with it, you should check it out: Reactome.org And even if you do know about this, you may not know that it also comes in green!  I did that as a Tip of the Week once–and check out Arabidopsis Reactome.  Of course, you’ll also find Reactome data in other places–like Entrez Gene, PID, and more.

And you should also help them out by answering their survey.  Here’s the request from the Reactome team:

Reactome Pathway Database User Survey

Reactome is committed to providing access to high-quality pathway information and helpful data analysis tools.  With this in mind, we are actively soliciting comments from the research community in order to assess community needs.  We are interested to hear about your experience with Reactome, and would like to know a bit about your background and research interests so that we can continue to improve the Reactome site and tools.

You can access the survey at: http://tinyurl.com/l48zzq

Thank you for taking part.

Robin Haw
Manager of Reactome Outreach

C’mon: you know the grant agencies and developers really want this kind of feedback. Help them out.

Paper compares interaction databases

venn_interactions.jpgI wish I had more time to go into this paper in more detail–but I wanted to let you know that the paper is out there now.  It came in my recent Nature Methods in paper version, and if I wasn’t crazy busy on a very cool project that we hope to launch this week I’d go deeper….

The paper is:  Literature-curated protein interaction datasets by Cusick et al. Nature Methods 6, 39 – 46 (2009)  2008 | doi:10.1038/nmeth.1284

I knew from the abstract that it was going to cause some conflama. And I was right.  Soon after an article in Bioinform addressed some of the issues.  Requires a subscription, but here’s the title and the link if you do have one:  Study Finding Erroneous Protein-Protein Interactions in Curated Databases Stirs Debate, by Vivien Marx.

This paper gets at a question that people ask us all the time–how do I know which database to use for X purpose?  So if your question is which database to use for protein interactions, you should read this paper and consider the points they make.   They don’t compare all protein interaction databases, of course–but for those they do examine (IntAct, DIP, MINT) they provide informative comparisons that you should consider for any database.  What does it contain?  What is it missing?  They have some nice Venn diagrams to illustrate the content.  The one I used here is just a representation of that, not attempting to be accurately proportional, go to the paper to see the real ones.

Our position is that you should use all of them, of course  :)  Project goals and funding issues, species specialties, scope…all of this impacts what will be in a database.  (In fact, please go to MINT and support their funding by signing their protest of funding cuts).

One point embedded in the paper caught my attention, though.  One major curation issue was that the species designation of the protein in the interactions was not clear.   I know sometimes this is a problem with the original source paper.  Sometimes it is a curation issue.  But this worries me because of the concern I raised with Wikipedia gene entries.  I made the point that there was no way to distinguish between human genes and mouse genes of the same name (MEF2/Mef2).  This could be true of similar genes in other species too–where the gene might not even be the same gene, just a naming coincidence. I can see it has arisen again.  But if we expect to rely on Wikification projects like Gene Wiki for more and more, I think that would need to be addressed.

Tip of the Week: Discovering Chemicals-Gene-Diseases Interactions w/ CTD (or Google)

ctdThe Comparative Toxicogenomics Database (or CTD) is an excellent database to find information on chemical-gene-disease interactions. It is a manually curated database of chemical-gene interactions, chemical-disease and gene-disease associations. At your fingertips you can find information about chemicals, interacting gnees, inferred diseases, pathways, references and news. It’s worth a look. And you can use Google to quickly search the database. Check out this week’s tip to find out more about the database and using Google to search it quickly.

New and updated Online Tutorials fo MINT and Reactome

OpenHelix today announced the availability of a new tutorial suite on MINT, a highly used database of protein-protein interactions, and an update to the Reactome tutorial. MINT is a collection of molecular interaction databases that can be used to search for, analyze and graphically display molecular interaction networks from a wide variety of species. Reactome is a knowledgebase of biological processes that is a high quality, deeply curated assembly of information about biological pathways and their components, including both biological and chemical entities.

The tutorial suites, available for single purchase or through a low-priced yearly subscription to all OpenHelix tutorials, contain a narrated, self-run, online tutorial, slides with full script, handouts and exercises. With the tutorials, researchers can quickly learn to effectively and efficiently use these resources. These tutorials will teach users:

MINT

  • how to search for protein interaction data in MINT
  • how to search for protein interaction data in MINT
  • how to search for inferred human interaction data in   HomoMINT
  • how to search Domino for peptide domain interactions
  • to edit and manipulate interaction data in the MINT viewer

Reactome

  • to navigate through the high-quality biochemical pathway information in Reactome
  • how to find diagrams and details about biological pathways
  • ways to link to information about specific pathways and participating molecules
  • to use the Reactome Mart interface to generate custom queries of the underlying database

To find out more about these and other tutorial suites visit the OpenHelix Tutorial Catalog and OpenHelix or visit the OpenHelix Blog for up-to-date information on genomics.

About OpenHelix
OpenHelix, LLC, (http://www.openhelix.com) provides the genomics knowledge you need when you need it. OpenHelix currently provides online self-run tutorials and on-site training for institutions and companies on the most powerful and popular free, web based, publicly accessible bioinformatics resources. In addition, OpenHelix is contracted by resource providers to provide comprehensive, long-term training and outreach programs.

Open source molecular modeling–finally?

My Bio SmartBrief newsletter today had a reference to a paper in a rather…um…obscure journal. Maybe it is just something I have missed over the years, but the Journal of the Royal Society Interface has really just never come across my desk before. Nevertheless, Wired seems to think this software is finally meeting our needs in biological modeling. Finally?

The open-source software movement has finally met the world of biological modeling.

Both a language and a program, “little b” gives systems biologists an infrastructure for building and sharing models of cellular activity.

Ok–this may be fabulous software. I’ll have a look. But to say that this is the one we have been holding our breath for is rather presumptuous. I’m not paying $49 for the paper, so I can’t assess it from the text. I will go and evaluate it at the developer’s site. For software evaluation I do read the papers (unless they cost $49), but I don’t believe anything until I kick the tires quite a bit anyway.

But from the breathless Wired article I can’t see why this is the solution rather than GenMapp, or BiologicalNetworks, or Cytoscape, or NAViGaTOR, or VisANT or….the half a dozen other that we are looking at for tutorial development. Or the ones I intend to learn about at the ISSB meeting in Sweden next month. The choice of tutorials there had me stumped on which ones I could fit into my schedule.

This Wired line about the image they show cracked me up:

Image: Detail from a gene regulation network, courtesy of PNAS. Wouldn’t it be great not to have to duplicate this in every new model?

Um….I can reproduce most of that now with about 10 different tools. If I wanted to do it quickly with stored information I could go to MINT and check out the curated interaction data and their very cool MINT Viewer (you can watch me do that in a movie here). Well, except it doesn’t show a picture of the Golgi in the background. Is that what’s new–despite that being from some unreferenced PNAS paper that may have nothing to do with this software? I would bet if I asked most of these teams would let me load up a cell graphic in the background, or I could create a network and layer it in with my image editing software. But I don’t think that’s it.

I hope little b is great. But like most software in this field there are other options–and some tools are right for some tasks, others are right for other tasks, even when they are in the same space. As we say in the blogosphere, YMMV {your mileage may vary}.

Learn about protein-protein interactions.

Bioinformatics.org is a great organization and web site (disclosure: I’ve taught an online course with them :D) and they regularly have online course in the field of bioinformatics that are more in the theory and analysis area of bioinformatics (where ours is more in the use and access of resources). If you need bringing up to speed on protein-protein interactions, there is room in next week’s course on said subject.

We have training in several protein-protein interaction resources such as STRING, soon MINT, so this bioinformatics course seems a nice complement. To learn more about the course, follow me under the fold…

Continue reading

Tip of the Week: Molecular INTeraction Database (MINT)

mint_thumbnail.jpgMINT, the Molecular INTeraction Database, is so much fun to use. I know–there is high-quality curated information from the scientific literature. And that’s the real point. But quite frankly, I just love to examine the protein-protein interactions in the MINT viewer. In this brief (about 3 minutes) exploration of some of the high-level features of MINT I will offer a taste of how fun and informative this resource is.
mentuccia_small.gif
A team at the University of Rome brings MINT to you. Check it out here: http://mint.bio.uniroma2.it/mint/

But at just a few minutes, we can’t provide the full detail about how to understand the graphics and how to use the site most effectively. We have a full tutorial on MINT that you might want to examine if this is a tool you would want to use on a regular basis.

And for more detail on the background and goals of MINT you should check out their paper. From their abstract:

Over the past few years the number of curated physical interactions has soared to over 95000.

That’s a lot of MINT. If you are like me and the previous owners of your house planted mint, you’ll understand the scope :)

Speaking of the Bork lab…

In the previous post I briefly mentioned a paper coming out of the Bork lab at EMBL.

The lab just made public a new tool: STITCH, “a resource to explore known and predicted interactions of chemicals and proteins.” This is a sister project to STRING, a great tool for exploring the interactions of proteins