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Today while working on a project I needed to get access to the Gene Ontology hierarchy. While there a number of GO browsers such as Amigo, I needed access to the raw data to generate a graph that I could then slice and dice. A few minutes with Python led to a simple solution.

The program parses the OBO 1.2 formatted GO data file (either by directly downloading it or from a local file) and outputs a flat dictionary listing the term ID’s, names, namespace etc and a network representation of the GO hierarchy in ncol format. It uses a simple  (and relatively non-robust) class to represent the data as an undirected graph (not really correct), though it’d be easy to use something like igraph to start doing some real network analysis. It’s certainly not a comprehensive solution, but I thought I’d put it out there.

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Last year, John Van Drie and I published two papers (here and here) on the Structure Activity Landscape Index, (SALI) which is a way to view SAR data as a network of compounds. Along with the paper ,I put up a simple Java application (licensed under the LGPL) to generate and explore these networks. – you only need to provide a file containing SMILES and activities. It’s based on ZGRViewer – a very slick GUI for Graphviz generated networks. I finally got around to reorganizing the code and putting it up on a GitHub repository. You can get more details of the application and the last stable version here.

sali-ss

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Using the model deployment and prediction service, I put up the two linear regression models I had built so far (described in more detail here) While REST is nice, a simple web page that allows you to paste a set of SMILES and get back predictions is handy. So I whipped together a simple interface to the prediction service, allowing one to select a model, view the author-generated description and a get a nice (sortable!) table of predicted values. View it here. As noted in my previous post it’s not going to be very fast, but hopefully that will change in the future.

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The folks at the EBI have been doing some great work on the CDK. A major effort is underway to revamp JChemPaint and part of this involves improving the rendering of 2D depictions. While not complete I rebuilt a version of the CDK 1.2.x branch with the latest rendering code from the jchempaint-primary branch and updated the CDK web service. The results are much nicer, though there’s scope for improvements. See for example

http://rguha.ath.cx/~rguha/cicc/rest/depict/c1ccccc1
http://rguha.ath.cx/~rguha/cicc/rest/depict/C1CCCCC12CCCCC2
http://rguha.ath.cx/~rguha/cicc/rest/depict/CC(=O)OC1=CC=CC=C1C(=O)O
http://rguha.ath.cx/~rguha/cicc/rest/depict/c1ccccc1CC=CC%23N

Thanks to Gilleain and Egon for pointing me in the right direction. Anybody using this service should see the new depictions automatically

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The current version of the REST interface to the CDK descriptors allowed one to access descriptor values for a SMILES string by simply appending it to an URL, resulting in something like

http://rguha.ath.cx/~rguha/cicc/rest/desc/descriptors/
org.openscience.cdk.qsar.descriptors.molecular.ALOGPDescriptor/c1ccccc1COCC

This type of URL is pretty handy to construct by hand. However, as Pat Walters pointed out in the comments to that post, SMILES containing ‘#’ will cause problems since that character is a URL fragment identifier. Furthermore, the presence of a ‘/’ in a SMILES string necessitates some processing in the service to recognize it as part of the SMILES, rather than a URL path separator. While the service could handle these (at the expense of messy code) it turned out that there were subtle bugs.

Based on Pats’ suggestion I converted the service to use base64 encoded SMILES, which let me simplify the code and remove the bugs. As a result, one cannot append the SMILES directly to the URL’s. Instead the above URL would be rewritten in the form

http://rguha.ath.cx/~rguha/cicc/rest/desc/descriptors/
org.openscience.cdk.qsar.descriptors.molecular.ALOGPDescriptor/YzFjY2NjYzFDT0ND

All the example URL’s described in my previous post that involve SMILES strings, should be rewritten using base64 encoded SMILES. So to get a document listing all descriptors for “c1ccccc1COCC” one would write

http://rguha.ath.cx/~rguha/cicc/rest/desc/descriptors/YzFjY2NjYzFDT0ND

and then follow the links therein.

While this makes it a little harder to directly write out these URL’s by hand, I expect that most uses of this service would be programmatic – in which case getting base64 encoded SMILES is trivial.

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As part of my work at IU I have been implementing a number of cheminformatics web services. Initially these were SOAP, but I realized that REST interfaces make life much easier. (also see here) As a result, a number of these services have simple REST interfaces. One such service provides molecular descriptor calculations, using the CDK as the backend. Thus by visiting  (i.e., making a HTTP GET request) a URL of the form

http://rguha.ath.cx/~rguha/cicc/rest/desc/descriptors/CC(=O)

you get a simple XML document containing a list of URL’s. Each URL represents a specific “resource”. In this context, the resource is the descriptor values for the given molecule. Thus by visiting

http://rguha.ath.cx/~rguha/cicc/rest/desc/descriptors/
org.openscience.cdk.qsar.descriptors.molecular.ALOGPDescriptor/CC(=O)C

one gets another simple XML document that lists the names and values of the AlogP descriptor. In this case, the CDK implementation evaluates AlogP, AlogP2 and molar refractivity – so there are actually three descriptor values. On the other hand something like the  molecular weight descriptor gives a single value. To just see the list of available descriptors visit

http://www.chembiogrid.org/cheminfo/rest/desc/descriptors

which gives an XML document containing a series of links. Visiting one of these links gives the “descriptor specification” – information on the vendor, version, reference to a descriptor ontology and so on.

(I should point out that the descriptors available in this service are from a pretty old version of the CDK. I really should update the descriptors to the 1.2.x versions)

Applications

This type of interface makes it easy to whip up various applications. One example is the PCA analysis of compound collections. Another one I put together today based on a conversation with Jean-Claude was a simple application to plot pairs of descriptor values for a collection of SMILES.

dppss1

The app is pretty simple (and quite slow, since it uses synchronous GET’s to the descriptor service for each SMILES and has to make two calls for each SMILES – hey, it was a quick hack!). Currently, it’s a bit restrictive – if a descriptor calculates multiple values, it will only use the first value. To see how many values a molecular descriptor calculates, see the list here.

With a little more effort one could easily have a pretty nice online descriptor calculation application rivaling a standalone application such as the the CDK descriptor GUI

Also,if you struggle with nice CSS layouts, the CSS Layout Collection is a fantastic resource. And jQuery rocks.

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First Steps with Git

With all the stuff I’ve been hearing about Git I’ve been looking to play around with it. While I have been hosting my own Subversion repo on my office machine, the use of GitHub seemed like a good way to play with Git and also have a stable external repo.

So right now the CDKDescUI project has been shifted into Git and is located here. I’ve also shifted my REST web services here

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