[BioC] DEGraph graph format?

Oliver Ruebenacker curoli at gmail.com
Sun Jun 10 23:27:24 CEST 2012


     Hello Laurent,

On Sun, Jun 10, 2012 at 4:21 PM, laurent jacob <laurent.jacob at gmail.com> wrote:
> Hi Oliver,
>
> 2012/6/10 Oliver Ruebenacker <curoli at gmail.com>:
>
>>  Can you explain some more why you choose not to use Rredland? It
>> seems almost certainly relevant for the design of a BioPAX package.
>> Did the issue have to do with separating the actual reaction network
>> from other types of information?
>
> If I remember well, I wasn't sure how to reconstruct the network
> structure form Rredland output, in particular how to recover the edges
> from the parsed BioPAX statements. It's not that the parsing done by
> Rredland was problematic, it's more that additional work (which seemed
> non-trivial to me at the time) was required to convert the output to
> graph objects.

  What kind of graph you are constructing? Is it a bi-partite graph
where every physical entity is a node and every reaction is a node,
and you connect every reaction with its reactants, catalysts and
products? In BioPAX Level 2, getting that graph was quite tricky, but
Level 3 is much easier (although catalysts ad modulators are still a
bit awkward).

> Are you planning to develop a bioconductor package or an independent
> Java parser? If you plan on using Java, you may want to look at what
> the mskcc people did for their Cytoscape plugin, which I used for my
> own package: http://cbio.mskcc.org/cytoscape/plugins/biopax/

  I'd love to submit to Bioconductor, if that is not too difficult.

  The Cytoscape plugin is based on PaxTools, the official BioPAX Java
library. The reason I'm not using PaxTools is that I'm combining
BioPAX data with other data, such as SBPAX, which is not yet part of
BioPAX (although hopefully will be soon), and is therefore not (yet)
supported by PaxTools.

     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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