Tag Archives: pathways

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.

Video Tip of the Week: Caleydo for gene expression and pathway visualization

Recently while watching the #bioinformatics tag on Twitter I saw Khader Shameer mention Caleydo.  I was instantly hooked at the very clever visualization strategy that they are using to provide more surface area for examining the data you are interested in viewing.  Their specific topics are pathways and gene expression, but it got me thinking about various data types that I would like to see connected in this way. This week’s Video Tip of the Week is about this sofware.

To skip right over to Caleydo and start trying it out, go here: http://www.caleydo.org/

Caleydo delivers a 3D representation of the expression and pathway data.  The main user interface has an area that is a box.  They call it a bucket, but in my head buckets are round, so I think of this as a box.  On the floor of the box you have a graphic.  But because you also have 4 interior surfaces of the box you have 4 more places to display and link the data.  You can have a heat map microarray representation on one side, and various pathways associated with the genes in that microarray on the other sides.

There’s a short systems biology Application Note in Bioinformatics that describes the framework and gives an overview of the tool.  But there’s also a more detailed paper over at their publication site that will get you started (that 2010 paper for the Visualization conference in Taipei).

My computer is a bit underpowered, but I was able to load their webstart version and begin to look around.  They provide some sample data you can select and examine.  For the movie this week, though, I was unable to load that and run the recording software at the same time.  So mostly it’s an introduction to the concept and the site.  You’ll have to go over and load it up yourself to try it out.  If the webstart version doesn’t work for you, there are a couple of other download options for different platforms.

The Caleydo team has also done a YouTube overview of the features that you can examine.


So try out this visualization strategy and see what you think.  I really like the concept.


Streit, M., Lex, A., Kalkusch, M., Zatloukal, K., & Schmalstieg, D. (2009). Caleydo: connecting pathways and gene expression Bioinformatics, 25 (20), 2760-2761 DOI: 10.1093/bioinformatics/btp432

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.

Tip of the Week: NCBI's New BioSystems Resource

tip_NCBI_BioSystems At the Biocuration meeting that I attended back in April, Jim Ostell of NCBI announced that they would soon be releasing a new resource on biological networks. A few weeks ago a friend  alerted me that NCBI had released their new BioSystems resource (thanks for the heads-up, Cyndy!) BioSystems is a cool resource that take nice advantage of the interconnectedness of all of NCBI’s Entrez resources to give great pathway information – either species-specific pathways or general pathways with extensive links to other NCBI databases as well as outside resources. NCBI describes their new resource (in part) like this:

A number of databases, such as KEGG and BioCyc, provide diagrams showing the components and products of biological pathways along with corresponding annotations and links to literature. The NCBI BioSystems Database was developed as a collaborative and complementary project to (1) serve as a centralized repository of data; (2) connect the biosystem records with associated literature, molecular, and chemical data throughout the Entrez system; and (3) facilitate computation on biosystems data.

There is NO WAY I can cover all that BioSystems has to offer in this 5 minute tip, but fear not – not only is NCBI’s documentation on BioSystems quite nice, we here at OpenHelix are already at work on a full BioSystems tutorial! We’ll keep you posted on that project, but for now – enjoy the tip & check out the resource for yourself when you’ve got some time.

Reactome new release, now with axon guidance!

Last night I had coffee with good friends in Davis Square and I mentioned that we had this blog.  One of the friends (a linguistics scholar) seemed excited by the prospect until I told her the topic.  She’s not nearly as excited by new software and scientific data as I am :)

It cracked me up this morning when I read the Reactome news letter–my first thought was: cool, axon guidance pathways!  And I imagined my friend’s bemused look….

Anyway, there’s a new Reactome release.  Here’s some of the new stuff content-wise:

New content. As part of a project to annotate the general process of cell motility and its involvement in key biological processes, Version 29 introduces a new topic, Axon guidance, with material now available for NCAM signaling in neurite outgrowth. Pathway topics updated with new curated events in this release include: Synaptic transmission (Glutamate Binding, Activation of AMPA Receptors, and Synaptic Plasticity), DNA Repair (regulation of FANCD2 and FANCI activity in the Fanconi Anemia pathway), and pathways whose dysfunction plays a major role in the development of diabetes (Regulation of insulin secretion and Unfolded protein response). With the annotation of G-coupled protein receptors (GPCRs) for eicosanoids, leukotrienes, nucleotide-like (purinergic) molecules, LPA and lysosphingolipids, opsins, secretins, and GABA and related molecules (class C/3 receptors), our annotation of interactions between GPCRs and their ligands is essentially complete. The Telomere Maintenance pathway has been revised in this release. Updated release statistics are available.

If you are interested in keeping up with Reactome their mailing list is here: http://mail.reactome.org/mailman/listinfo/reactome-announce

Pathway drawing standards: SBGN notations

We are thinking quite a bit about pathway tools these days. I got a jolt of input on them from the ICSB meeting recently, too. As I continue to progress through my meeting notes I’ll be checking out more tools and writing about them.

sbgn_logo.jpgOne of the things that seemed new and important (well, to me at least) was the first release of a set of standards for drawing pathway diagrams. During this meeting they announced the release of 1.0 of the SBGN notations (also known as Level 1; more levels are anticipated as this progresses). SBGN is Systems Biology Graphical Notation. You can access the SBGN site here: http://www.sbgn.org/

The idea is that if we can standardize our representations of pathways we can all be sure that the meanings are the same for arrows, and boxes, and so on. For example, if I draw a pathway with an arrow, my arrow means the same thing as your arrow in your pathway diagram.

What the SBGN team says on their homepage:

SBGN defines a comprehensive set of symbols with precise semantics, together with detailed syntactic rules defining their use and how diagrams are to be interpreted.

So this is kind of like Gene Ontology for systems and pathway diagrams. Not only is it increasing the clarity of the diagrams, it will guide software development so that software for generating diagrams and analytical tools can work in this framework as well.

There are examples on the web site. Check out the document on the specifications (a big PDF), too–lots of detail on what, how, and why this is important. They want feedback on this. You can also check out the associated SBGN wiki with more details and the SBGN forum for interaction with the team.

Tip of the week: list of genes–>pathways

reactome_skypainter.jpgIn this week’s tip I wanted to talk about a tool that offers a handy way to visualize the items in a list of genes that you might have on pathway diagrams. Reactome offers a tool called SkyPainter that allows you to enter a list of genes which is then analyzed statistically for genes in certain pathways. But then–and here’s the cool part–you also get a diagram of the pathways with the over-represented genes painted on a map of their pathway universe. See–SkyPainter. Anyway, it is a tool I have liked for years and I’ve been thinking a lot more about lists of genes and pathway representations. So I wanted to share that with you. This ~4 minute movie shows you how to access SkyPainter at Reactome and get started using it. Have fun!

Software bonanza…

Still enjoying the ICSB meeting, and it is a gorgeous fallish morning in Göteborg. What a great city and terrific people here. Not entirely sure I want to come home….

My brain is approaching “full” already, and there are still several days to go. I’ll have a lot of tools to talk about in the coming weeks as I check more of them out. But I wanted to talk about a couple of neat tools that I have heard about so far. First–CellDesigner 4.0, that I mentioned the other day, was a good choice of tutorials to attend for sure. You can access their tutorial material here. Turns out they are also about to release a web-based version of this that will be a collaborative community editing tool for networks and pathways. It is called Payao–which I’m told means a type of “fish-aggregating device” according to their poster. I was unable to catch the poster authors so far to discuss it further, but it looked like a neat tool. I can’t find a release on the web yet and there was no URL on the poster. I’ll try to track them down again today.

Update: Found it here http://celldesigner.org/payao/payaopreview.html

Another fun tool (which I haven’t had a chance to use much yet) is BioMyn. The idea behind BioMyn is that it is something like a Google search for systems biology and other relevant biological data types. It aggregates a lot tools into a single search, here’s a partial list: ensembl, MINT, GAD, HPRD, Corum, InterPro, PDB, OMIM, GO, Reactome, KEGG, UniProt, HiMap, IntAct, GNF, and DIP. I spoke to Fidel Ramirez, the creator, about this tool and he was very eager to have users and feedback on this new beta phase. He was saying that people have suggested the results link should be re-organized a bit. If you do a search you get a list of results and some context. The link at the top goes to your “best” resource hit–leaving BioMyn. But if you click the link at the bottom of the result ( View all annotations for ) you go to the aggregated results in BioMyn. Organized into a collection of data in tabs, you can find a wealth of information on this gene. You can find gene links, of course, but also diseases, pathways, interactions, GO terms, and on and on. Anyway–check it out. And keep in mind it is beta. Feel free to offer feedback here and I will pass it along to the developers–they don’t have a feedback link on the site yet. But they do have a blog, I suppose you could put comments over there. In fact, I’ll suggest that to the team today if I see them.

Another Wiki, WikiPathways

ResearchBlogging.orgPLoS Biology reports today on WikiPathway. The paper entitled “WikiPathways: Pathway editing for the people,” announces a new wiki for the ‘public curation’ of pathway data. The authors argue that

 The exponential growth of diverse types of biological data presents the research community with an unprecedented challenge to keep the flood of biological data as accessible, up-to-date, and integrated as possible.

I agree with this. We’ve seen it here and mentioned it many times, the growth of data is exponential and difficult to keep track of. The proposed solution for pathway data, as there has been for other data types and curation that I’ve written about lately, is a wiki: WikiPathways to be exact. The authors have high hopes for this wiki, as they state:

WikiPathways will be a powerful resource for the research community and a vital forum for pathway curation, And we are hopeful that it will serve as an example for how the continuing flood of biological data can be managed and utilized by the community to irrigate future hypotheses and discoveries

I’ve already made known my “skeptical optimism” for wikis for biological data known in a previous post, reading this later paper, that would still apply here. But right now I’m not going to write beyond that, I’m just going to point you to this paper and wiki. Later (this week, next at the latest) I’ll be critiquing this paper more fully and more generally look at this trend currently to use wikis for community curation and documentation of biological data and databases.

Pico, A.R., Kelder, T., van Iersel, M.P., Hanspers, K., Conklin, B.R., Evelo, C. (2008). WikiPathways: Pathway Editing for the People. PLoS Biology, 6(7), e184. DOI: 10.1371/journal.pbio.0060184

KARG: Knowledgebase for Addiction Related Genes

I was perusing the new PLoS Computational Biology just now, with my hands gripped to my coffee mug. I spotted this article:
Genes and (Common) Pathways Underlying Drug Addiction by Li et al. I was wondering if the genes that direct me to coffee each morning were identified. But it doesn’t look like they covered coffee. The list of Addiction Related Drugs from their site has other plants. Alas.

To visit the new database, go here: KARG.