[BioC] BioPAX/SBPAX import for MicroArray Analysis and Hypothesis Building

[Oliver Ruebenacker]

     Hello Tim,

On Thu, May 31, 2012 at 5:53 PM, Tim Triche, Jr. <tim.triche at gmail.com> wrote:
> this seems clever, although I could swear that an existing package handles
> graphical models of similar sorts.

  We could turn BioPAX/SBPAX into R graphs similar to the way rsbml does it.

  I wonder if there already are packages for using R graphs
representing biological connections to model differential expression
data? Then we may be able to use these.

> but if the structural priors can be automatically pulled in (however that
> might happen) and updated it would be cool as hell.

  Such data could be made available as SBPAX. BioPAX/SBPAX are
excellent for merging data from multiple sources. Can you recommend
any significant providers of such public data?

  Thanks!

     Take care
     Oliver

>
>
> On Thu, May 31, 2012 at 2:47 PM, Oliver Ruebenacker <curoli at gmail.com>
> wrote:
>>
>>     Hello,
>>
>>  I am exploring the idea of creating a package to import pathways as
>> BioPAX/SBPAX (Level 3) data to analyze various measurements. In
>> particular, differential microarray measurements could be used to
>> identify upstream pathway nodes that seem to play a critical role in
>> explaining the observed differences.
>>
>>  The basic idea is very simple: consider a pathway that contains
>> reactions A -> X, B -> X and B -> Y. If measurements show an increase
>> in X, but not in Y, this would suggest an increase in A. If, however,
>> we see increases of both X and Y, then this would point to an increase
>> in B. Analogous considerations apply to nodes upstream of A and B.
>> Negative correlations (by inhibition or depletion) will also be
>> included. Consider this applied to a large network and a large set of
>> measurements, which requires statistical tools to identify the most
>> relevant upstream nodes.
>>
>>  There are people using similar methods on similar data relying on
>> quite simple evaluation functions and turning it into a profitable
>> business.
>>
>>  We can start with a simple prototype that can be created and
>> deployed as quickly as possible as proof of concept to find interested
>> parties. If there is sufficient interest, a more sophisticated version
>> can be built.
>>
>>  Different implementation approaches are possible. It seems to be
>> simple and efficient to use rjava and have the reaction network
>> extracted from BioPAX/SBPAX by a Java package that uses OpenRDF Sesame
>> Rio (i.e. a small fraction of Sesame dealing with RDF graph
>> representation and I/O).
>>
>>  Any comment or show of interest is greatly appreciated.
>>
>>  Thanks!
>>
>>     Take care
>>     Oliver
>>
>> --
>> Oliver Ruebenacker
>> Bioinformatics Consultant
>> (http://www.knowomics.com/wiki/Oliver_Ruebenacker)
>> Knowomics, The Bioinformatics Network (http://www.knowomics.com)
>> SBPAX: Turning Bio Knowledge into Math Models (http://www.sbpax.org)
>>
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>
>
>
>
> --
> A model is a lie that helps you see the truth.
>
> Howard Skipper
>



-- 
Oliver Ruebenacker
Bioinformatics Consultant (http://www.knowomics.com/wiki/Oliver_Ruebenacker)
Knowomics, The Bioinformatics Network (http://www.knowomics.com)
SBPAX: Turning Bio Knowledge into Math Models (http://www.sbpax.org)