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RE: Notes from informal Demo F2F

From: Eric Neumann <eneumann@teranode.com>
Date: Tue, 6 Mar 2007 11:29:33 -0500
Message-ID: <A3970D83EC72E84B8D2C2400CD6F0B9FE9B323@MI8NYCMAIL16.Mi8.com>
To: "Alan Ruttenberg" <alanruttenberg@gmail.com>, public-semweb-lifesci@w3.org

At one point during the informal F2F, the folks on the call (Karen Skinner, Eric P, John Barkely, Scott Marshall, Eric N, ?) were cut off from the conference, but we ended up having a discussion amonst ourselves, where we came up with a few suggestions regarding the demo:

- it might be compelling to use enough data (already known facts) to help make some interesting associations (Scott M's comment of 'manufactured serendipity'), which could then be annotated and used to propose hypotheses.
- use existing and familiar sources of genes and diseases (e.g., Entrez-Gene, Uniprot, etc, around AD/PD) for deeper data aggregation to show how RDF and SPARQL (this may already be what some of you are planning on doing)
- As part of the scernario using the known aggregate of facts, add a few *select* hypotheses (triple graphs), that would make major connections with the rest of the graph that would function as a "bridge" across the data and models; Show the new insights from this merged compositeby re-applying queries that now retireve more connections. One example Karen had was around the MPTP/MPP+ mechanism for some forms of PD. 

The latter point will probably need to be "manufactured", since we cannot rely on trying to uncover real scientific insights in time for this demo-- would be nice though!

It was also apparent that we need to identify what the specific "aha" or "cool factor" is in the demo when shown to the select audience; it appears to me taht it should be about the RDF or OWL nature of the data, federated SPARQL querying, and ability to add new data or annotations and get even more out of the construct.

-- 2 from those who called in.
Eric


-----Original Message-----
From: public-semweb-lifesci-request@w3.org on behalf of Alan Ruttenberg
Sent: Mon 3/5/2007 10:35 PM
To: public-semweb-lifesci@w3.org
Subject: Notes from informal Demo F2F
 

Summary:

We reviewed the use case, and then, starting in one area of the use  
case - the connection between ADDL and impairment of long term  
potentiation deficits - highlighted on page 2 of the updated use case  
[1] - and started to trace out a series of steps that lead towards  
determining relevant sets of gene  and then to images of expression  
of those genes. Along the way we reviewed web pages and databases to  
verify what information was available. We then collected a list of on  
line databases that would enable
the kinds of queries we were exploring.

[1] http://esw.w3.org/topic/HCLSIG_BioRDF_Subgroup/Demo_Thoughts/ 
Alzheimer%27s_Proposal? 
action=AttachFile&do=get&target=AD_PDUseCase_02-26-07.pdf

Start:

Hypothesis+Abeta -> ADDL (SWAN. Note that these areas of SWAN are not  
yet populated but June and Gwen are working on this).

We attempted to linking ABeta to LTP, but this did not find the  
requisite links. What we did was:

Go to http://senselab.med.yale.edu/senselab/modeldb/. Search for  
"ltp" (could also search for "long term potentiation"
This is a text search, and the matches are typically against the  
titles of citations.
Each result links to a model, which lists some cell types, some  
receptor families, some transmitters.

We reviewed the receptors and searched for them in NeuronDB but did  
not find links to processes such as long term potentiation.

--- Starting over

Go to http://senselab.med.yale.edu/BrainPharm/eavData.asp? 
db=1&c=122&o=5904
Links from Alzheimer's disease to  CA1 Pyramidal Neuron

Click on CA1 Pyramidal Neuron
Link to http://senselab.med.yale.edu/BrainPharm/NeuronDB/ 
ndbEavSum.asp?id=5588&mo=4&re=

CA1 Pyramidal Neuron Extracellular Elements : Abeta (current I A)
CA1 Pyramidal Neuron Intrinsic Currents : I A. Click on I A.

http://senselab.med.yale.edu/BrainPharm/eavData.asp?o=5545
Links to K+

Need to know that current of K+ is carried by Potassium Channels.

However, even though some text indicates LTP, there is no explicit  
link. We do have a link from neurons of interest
to genes however, if we are able to look up proteins associated with  
potassium channel function.
Browse GO we do find these associations.

---- Approach using LTP as a key from a different direction.

There is a mesh term
http://www.nlm.nih.gov/cgi/mesh/2007/MB_cgi?mode=&term=Long-Term 
+Potentiation&field=entry

We can link to pubmed papers using mesh term headings.

http://www.ncbi.nlm.nih.gov/entrez/query.fcgi? 
CMD=search&DB=pubmed&term=Long-Term+Potentiation%5Bmh%5D&cmd

There is also Potassium Channel
http://www.nlm.nih.gov/cgi/mesh/2007/MB_cgi?mode=&term=Potassium 
+Channels&field=entry
and Pyramidal cells
http://www.nlm.nih.gov/cgi/mesh/2007/MB_cgi?mode=&term=Pyramidal 
+Cells&field=entry

So if we have a Pubmed -> Mesh mapping, we are able to use this to  
navigate from mesh term to mesh term,
for example, from LTP to cell types or to channel types.

This also requires that we have the MESH tree encoded. Note, however,  
that this MESH->MESH links are potentially unreliable
as they could be the product of unrelated discussions in the paper  
used to do the mapping.

--- From pubmed to genes.

We can also go from pubmed to gene. This is seen in the user  
interface via the "links" button on a pubmed abstract page.
e.g.
http://www.ncbi.nlm.nih.gov/entrez/query.fcgi? 
db=pubmed&cmd=Retrieve&dopt=AbstractPlus&list_uids=17251421&query_hl=5&i 
tool=pubmed_docsum

Choose links, then gene, then you get:

http://www.ncbi.nlm.nih.gov/entrez/query.fcgi? 
itool=pubmed_AbstractPlus&db=pubmed&cmd=Display&dopt=pubmed_gene&from_ui 
d=17251421

The mapping of pubmed -> gene is not in the pubmed records, but is  
kept on the gene side.
There are entries in the Entrez gene asn or xml record, as well as  
the generifs, which associate a gene with a paper.

Along with the Gene ontology, we now have two ways to navigate from  
"Potassium channel" to gene.

-- From gene to brain region

We can get BrainRegion from gene in a number of ways:

Using expression data: The Allen Brain Map has, for a select group of  
regions and structures, lists of genes
expressed in those structures. Some of these are at:

http://community.brain-map.org/confluence/display/DataAnno/Home

Others can be scraped from the results of queries at http://brain- 
map.org/welcome.do (click on the "Anatomic Search" tab)
(Alan has these)

Similarly, Gensat (ftp://ftp.ncbi.nih.gov/RawData/ 
GENSAT-20050125.xml.gz) Has images associated with genes
and annotations that say which areas/cell types have which patterns  
of expressions of those genes.
(Alan has these)

--- From Cell type to brain region.

In addition to the mappings implicit in Gensat,
BAMS  http://brancusi.usc.edu/bkms/xml/swanson-98.xml has mappings of  
cell types to brain regions

-- Another route for getting Alzheimer related genes:

We can also get from Alzheimer to gene via Alzgene
There is a popup of genes on http://www.alzforum.org/res/com/gen/ 
alzgene/default.asp, which records
studies which find associations between mutations of these genes with  
Alzheimer disease.

--- Some other resources

We will want human to mouse gene mappings for better navigating from  
pubmed.
Available at:  http://www.ncbi.nlm.nih.gov/entrez/query.fcgi? 
db=homologene

For linking gene to protein and protein products such as cleaved  
proteins, June has started curating these from various sources.
Uniprot has such mapping, it is only textual. See, e.g.,  http:// 
www.pir.uniprot.org/cgi-bin/upEntry?id=P05067. Look for the  
"contains" field.

Another resource for relating phenotype, process to genes is the JAX  
Mammalian Phenotype ontology/
Associated with each phenotype, are the alleles/genes associated with  
the phenotype.

http://www.informatics.jax.org/searches/MP_form.shtml
For example, abnormal hippocampus function http:// 
www.informatics.jax.org/javawi2/servlet/WIFetch? 
page=mpAnnotSummary&id=MP:0001895

Gwen and Don will review the terms to see which would be relevant to  
processes associated with Alzheimers, and this gives us another
route to narrow/expand genes of interest.

Summarizing data sources which we will use for the next step of  
exploration. Some we have, some we need to acquire/convert to RDF.

Mesh
Pubmed -> Mesh Term
GO -> Associations (Genes)
Entrez Gene -> Pubmed
Entrez GeneRif (= gene->Pubmed)
NeuronDB/Brainpharm
Homologene
Alzgene (Alzheimer Disease -> Associated Gene)
JAX: Mouse Phenotpe -> Gene
Uniprot Gene-> splice form, gene product.
BAMS swanson-98.xml
Allen/Gensat gene->image, gene-> regions/expressed

Alan's comment: Process for conversion to RDF should be 2 step
1) Propose model, give sample entry for review
2) Upon agreement on model translate rests/load into triple store for  
query.

Action: Candidates for doing conversions: Alan, EricP, Matthias, Don 
(?) to talk and split tasks.
Action: Don and Gwen to review phenotypes
Action: June to curate trying to write pseudo-triples to make  
conversion to real triples easier.

-Alan
Received on Tuesday, 6 March 2007 16:31:07 UTC

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