Posted in cheminformatics, text mining, visualization, tagged annotation, database, go, network, pubchem, text mining, visualization on January 25, 2009|
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I’ve been working for some time with the PubChem Bioassay collection – a set of 1293 assays that cover a range of techniques (enzymatic, phenotypic etc.), targets and sizes (from 20 molecules to 200,000 molecules). In addition, some assays are primary, high-throughput assays whereas a number of them are smaller, confirmatory assays. While an extremely valuable collection, one of the drawbacks is the lack of curation. This has led to some people saying that the data is too noisy to be useful. Yes, the noise is a problem, but I think there’s still useful data to extract and model.
One of the problems that I have faced is that while one can perform a full text search for assays on PubChem, there is no form of annotations on the assays themselves. One effect of this is that it is difficult to link an assay to other biological resources (though for enzymatic assays, one can determine a Pubmed protein identifier). While working on my bioassay network project, I needed annotations and I didn’t want to do it manually.
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In a previous post, I described a simple web form to query and visualize the solubility data being generated as part of the ONS Challenge. The previous approach required me to manually download the data and load it into a Postgres database. While trivial from a coding point of view, it’s a pain since I have to keep my local DB in sync with the Google Docs spreadsheet.
This is very nice since I now no longer have to maintain a local DB and ensure that it’s in sync with Jean-Claudes results. Of course, there are some drawbacks to this method. First, the query page will assume that the data in the spreadsheet is clean. So if there are two entries called “Ethanol” and “ethanol”, they will be considered seperate solvents. Secondly, this approach cannot be used to include cheminformatics in the queries, since Google doesn’t support that functionality. Finally, it’s not going to be very good for large spreadsheets.
However, this is a very nice API, that allows one to elegantly integrate web applications with live data. I heart Google!
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