Hy Everyone,

My name is Milton and I'm starting to work with Graph database and would 
like if someone could give me some hints.

I work with Bioinformatics and I would like to integrate KEGG-Metabolic 
Pathways with Microarray data

Just to introduce my problem:
 - the Metabolic Pathways are graphs (~200) and each node are the genes, in 
my case.
 - the Microarray data, has multiple experiments, where each experiment is 
a list of genes (nodes) with a respective signal intensities (value)

What I'm planning to do is to integrated the gene intensity (values) for 
each experiment (microarray) with the nodes in the Metabolic pathways and 
include those pathways in the graph database.
In the end, if I have 5 experiments, I would have the same metabolic 
pathway in the graph database, but for each experiment with different 
values for each node (gene)

My final goal would be to make some queries in each experiment, and 
identify the differences of one pathway,  between the 5 experiments.

I would appreciate if someone could give some hint and tell me if I'm crazy 
in the idea to include the same pathway but related to different 
experiments, with different node values.

Thanks a lot,

Milton


On Friday, February 7, 2014 1:12:24 PM UTC-2, Eduardo Pareja Tobes wrote:
>
> Hey Michael, everyone
>
> I just noticed the existence of this group; I'm one of the Bio4j people 
> that Kimmen mentioned below. For anyone who doesn't know what this Bio4j 
> thing is, check the slides from Pablo Pareja presentation at FOSDEM this 
> past weekend: 
> http://ohnosequences.com/slides/fosdem-2014/bio4j-bigger-faster-leaner. 
>
> Good to see growing interest in this area, it's been ~4 years since we 
> started working on Bio4j with Neo4j and we were starting to feel a bit 
> lonely :) I do think that there are a lot of opportunities for 
> collaboration in this space!
>
>
>
> On Saturday, October 26, 2013 11:09:54 AM UTC+2, Michael Hunger wrote:
>>
>> Hi Wolfgang & others, 
>>
>> the plan is to run a graphs in biotech workshop in Berkeley in January. 
>>
>> Kimmen Sjolander works on a project (phylo4j) to assemble loads of 
>> information (ontologies, genetic, proteins, pathways, etc) into a huge 
>> graph. 
>> https://dl.dropboxusercontent.com/u/14493611/phylo4j-cypher%20models.pdf 
>>
>> In the past we ran the Graphs in Life Sciences Workshop with Lennart 
>> Martens & Thilo Muth in Ghent, Belgium with lots of interesting 
>> contributions: 
>> http://blog.neo4j.org/2012/11/graph-databases-in-life-sciences.html 
>> <http://www.google.com/url?q=http%3A%2F%2Fblog.neo4j.org%2F2012%2F11%2Fgraph-databases-in-life-sciences.html&sa=D&sntz=1&usg=AFQjCNHvRBQ7J76GcLa0Gf34I4sVQ-0KUg>
>>  
>> Esp. the metaproteonomics project by Thilo (source on google code, 
>> presentation in the blog was interesting). He also did a webinar last week: 
>> https://vimeo.com/77450061 
>>
>> There is also this nice GraphGist pathway model by Ben Butler-Cole: 
>> http://gist.neo4j.org/?24d0c8032389c7e52f9f (feel free to add your own 
>> models, it's simple) 
>>
>> And we started a (kind of quiet) google group for neo4j-biotech that I 
>> intended for people to discuss topic specific scientific details of their 
>> models and implementations. (http://groups.google.com/group/neo4j-biotech). 
>>
>>
>> Michael 
>>
>> Am 26.10.2013 um 03:19 schrieb Wolfgang Hoeck <[email protected]>: 
>>
>> > Hi Michael, met you @ GraphConnect in SF in Data Loading session. I am 
>> planning to introduce Neo4j to folks in my company within the 
>> Biotech/Pharma space in November. Would love to hear more about 
>> applications of Neo4j in this space. Anything you can share would be 
>> helpful. Biology is a highly connected data space, so graph databases 
>> should be able to have a great impact, but we have to be patient so we 
>> don't over promise and under deliver as seen too many times before. Just 
>> connecting data without a good model behind probably won't do :-) 
>> > 
>> > I can see applications in Competitive Intelligence, Business Process 
>> Modeling, System Configuration Management, Sample/Cell Line/Experiment 
>> Annotation System, Drug Target Database, etc. 
>> > 
>> > Many thanks in advance for any further insight in this space. 
>> > 
>> > -- 
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>>

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