Re: BioRDF [Telcon]

Hi All,

This is a fantastic use case, where semantically formal annotations  
will be absolutely required in order to resolve even a portion of the  
questions listed, if they are to cast a wide net across all the  
relevant information - e.g., primary data repositories (individual,  
as well as data warehouses and federated data resources), the  
literature, clinical trial reports, clinical records, etc.

This is exactly what I was trying to get at back in the late summer  
on the BIOONT Wiki.  The idea was to go into the literature to pull  
together several relevant papers collectively providing findings  
related to a broader question in neurodegenerative illness.  We'd  
then go through the papers - just at a high-level - and pick out the  
essential findings, expressing them using the PATO formalism http:// 
www.bioontology.org/wiki/index.php/PATO:Main_Page).  This requires  
expressing the observation made in the context of ontologically  
defined entities from the molecular on up through behavior.  In  
performing this task, one must determine which of the available  
community ontologies can cover the required domains.  It also helps  
to provide a clear categorical description of the type of data  
repositories that must be integrated and where they fit into the  
overall semantic landscape.  BioRDF would then define what exists for  
those domains that is publicly accessible - as is outlined somewhat  
in the BMC Bioinformatics manuscript.

I apologize for missing the meeting today.  I was ill and am slowly  
coming back.

Re: the BIRN Use Cases relevant to the HCLSIG Demo:
	As I mentioned in the TCon last Thursday, I've been working with the  
BIRN Ontology Task Force to assemble a public page providing the many  
use cases assembled by various BIRN research projects - all of which  
focus on drawing together information from disparate sources to  
address scientific questions related to Alzheimer's Disease,  
Schizophrenia, Parkinsonism, and MS (with Huntington's Disease and  
Autism being introduced over the past year or so).  Given the heavy  
neuroimaging focus on BIRN, many of the details of these use cases  
relate to seeking correlations between segmented geometries in  
various MRI, MRI/DTI, fMRI, light-microscopic, and EM images and  
other related data extending from genotype & gene expression on  
through behavioral & cognitive assessments.  Many of the active  
research projects in the BIRN involve the generation and analysis of  
neuroimaging data and associated experimental assessments - data that  
may be acquired in one lab, processed in another, and ultimately used  
for analysis by many.  Already there are 100s of TB of data on the  
BIRN infrastructure, though imaging researchers will recognize this  
is quite small, given that includes raw image data, and data in  
various stages of processing and analysis.

	BIRN's goal is to provide a high-capacity, high-throughput  
infrastructure to support this manner of collaborative research and  
to host the results for public use.  The components assembled to date  
consist of the following:
		1) a distributed query mediator posting queries across the 60+ site  
source data repositories - many of which are RDBMS-based.  A source  
repository needs to "register" with the mediator in order to be  
accessible during query resolution
		2) an ontology (BIRNLex) to provide a shared, formal expression of  
the required biomedical entities and processes that will support  
machine-parsing of semantic assertions defined on data via ontology- 
based annotation; note that the BIRN ontology draws heavily on the  
community ontology efforts throughput biomedicine, to avoid  
duplicating effort and ensuring maximal semantic integratability
		3) a storage grid (based on SRB) that includes a metadata catalog  
which can be linked to the mediator; when a query result tuple points  
to a binary object such as a 2D, 3D, or 4D image set stored on SRB,  
this can be returned to the querying application - whether its an  
interactive, end-user oriented query front end, or an automated  
process, such as a distributed image processing pipeline
		4) an XML Schema (XCEDE) and associated toolset for uniform  
exchange of data.  This can help to simplify and standardize the way  
in which the 3 resources above are put into practice, as well as  
provide a uniform view of BIRN-hosted information to the greater public.

	As I mentioned before, the BIRN project as a whole has focussed on  
providing this required infrastructure, tools, and data standards for  
the current BIRN participants.  Though the goal is for all of these  
resources to be publicly available, human resource limits have meant  
what is currently available via the BIRN infrastructure to the public  
is very limited.  There is an effort underway to address this issue.   
We on the Ontology Task Force have made our current draft ontology  
available publicly.  What is being assembled in that ontology is  
designed to support the use cases identified by the participating  
research labs.  These are grouped under "testbed" categories - two  
human focused - Morphometry BIRN (MRI & DTI-MRI) and Function BIRN  
(fMRI) - and one focussed mouse models of neurodegenerative disease -  
Mouse BIRN.  More recently, there have been efforts to include  
neuroimaging projects associated with the various North American  
primate centers, which brings in macaque, a species used extensively  
for various structure/function studies in the brain (see  
www.cocomac.org).

	As a preliminary to assembling a comprehensive and coherent listing  
of the use cases from throughout BIRN, I've assembled pointers to  
"some" of the use cases on the public BIRNLex page:
		http://xwiki.nbirn.net:8080/xwiki/bin/view/+BIRN-OTF-Public/Home

	I would say the following are all worth looking through:

	1) The recent Morphometry BIRN use case listed there on that page  
provides a since of the comprehensive nature of the questions being  
addressed in that project - in this particular case various ways of  
determining whether diagnosed depression can effect the onset and  
severity of AD.
	2) The link to the Function BIRN Use Cases below the table on that  
page provides a sense of the complex imaging & image associated  
metadata one must semantically represented in order to make effective  
use of fMRI data to answer a broad range of questions questions  
related to the structure & function (or malfunction) of the nervous  
system.
	3) The "3 BASIC LEVELS OF DATA MEDIATION" link, since it was  
assembled by the group in Mouse BIRN that works on the alpha- 
synuclein mouse model of PD.

	There are many, many more use cases than these, but it will probably  
be a while before I'm able to do better than this.  BIRN is large  
organization, and I'd want to make certain along with the Use Cases,  
we provide information on which are actually being pursued as  
research questions by BIRN-associated projects, so as to be able to  
indicate there is data related to that use case accumulating on the  
BIRN infrastructure, and the BIRN ontology has covered the relevant  
knowledge domains.

	I hope this is helpful.

	I will try to find time soon to get to more of the BIRN use cases,  
especially those supported by data and ontological graphs and  
directly related to the current PD use cases Don, Kei and others have  
included in the BMC Bioinformatics manuscript.

Cheers,
Bill
	
On Dec 11, 2006, at 11:03 AM, June Kinoshita wrote:

>
> Hi Susie,
>
> Elizabeth, Gwen and I have been working on a fairly elaborate use  
> case. To help the con call participants follow it, we've prepared  
> this simple outline:
>
> A hot topic in AD therapy is immunization - developing a vaccine or  
> antibody that will neutralize amyloid-beta peptide (Abeta), the  
> putative toxic agent that is hypothesized to cause Alzheimer disease.
>
> Problem: The first clinical trial was halted because patients  
> developed encephalitis.
>
> Question 1: Why did some patients but not all get encephalitis?
> Question 2: There is debate about whether Abeta is the toxic  
> entity; but assuming it is, what form is toxic? Abeta has been  
> reported as monomers, dimers, soluble oligomers, protofibrils,  
> insoluble fibrils.
>
> Research Challenge: If immunization therapy is to work, i.e. it  
> clears Abeta from the brain and does not cause encephalitis, one  
> needs to 1) identify the exact toxic form, 2) understand cause of  
> encephalitis (brain inflammation)
>
> In our use case, an investigator reads about the discovery of a new  
> form of Abeta, called Abeta*56, that is reported to cause memory  
> impairment in a mouse model of AD.
>
> Is Abeta*56 a good target for immunization therapy?
>
> Question: Is there human data to support that Abeta*56 is involved.
>
> A query of PubMed finds a paper reporting that a form of Abeta with  
> identical molecular weight, called ADDL, is elevated by as much as  
> 70-fold in human AD patients' cerebrospinal fluid. A hypothesis  
> about ADDL causing memory loss in AD is posted on Alzforum.
>
> Question: By what mechanism might Abeta*56 cause memory loss?
>
> The ADDL Hypothesis on Alzforum suggests that ADDL (= Abeta*56?)  
> disrupts LTP.
>
> Question: What is the mechanism of LTP, in a part of the brain that  
> is relevant to AD?
>
> The literature indicates CA1 hippocampal neurons, and A- and D-type  
> K channels are involved in LTP. BrainPharm data state that CA1  
> hippocampal neurons have A-channels.  What's more, the A-current is  
> reduced by Abeta.
>
> Question: Would an antibody directed against ADDL / Abeta*56  
> restore A-current in the mouse model hippocampal neuron (e.g. in an  
> organotypic slice prep)?
>
> A query locates an antibody to ADDL and where to obtain it.
>
> Question 2 is what determines vulnerability to encephalilitis among  
> immunized patients?
>
> A literature search finds interferon-gamma (INFG) may be a player.  
> This comes from both mouse and human trial data (need to check this).
>
> Question: Do polymorphisms in INFG, or differences in INFG  
> regulation, correlate with inflammatory response to vaccine?
>
> Question: Why did the mouse models not develop encephalitis in  
> preclinical studies?
>
> Our investigator queries pathway databases to identify the gene  
> network involved in IFNG regulation, and also SNP databases for  
> differences between mouse strains, mouse and human. He narrows down  
> a group of genes and queries the AlzGene database to see if any  
> gene association studies have shown a correlation between any of  
> these genes and AD risk.
>
> Our investigator proposes a study to genotype participants in the  
> failed vaccination trial to find out whether the encephalitis  
> response correlates with specific SNPs in the candidate genes.
>
>
> On Dec 8, 2006, at 3:16 PM, Susie Stephens wrote:
>
>>
>> Here's a reminder for Monday's BioRDF call.
>>
>> Date of Call: Monday December 11, 2006
>> Time of Call: 11:00am Eastern Time
>> Dial-In #: +1.617.761.6200 (Cambridge, MA)
>> Participant Access Code: 246733 ("BIORDF")
>> IRC Channel: irc.w3.org port 6665 channel #BioRDF
>> Duration: ~1 hour
>>
>> Agenda
>> Matthias Samwald and Alan Ruttenberg will be providing task updates.
>> Bill Bug, Elizabeth Wu and Scott Marshall will be discussing the  
>> scientific queries that they have been researching.
>>
>> Kind regards,
>>
>> Susie
>>
>
>

Bill Bug
Senior Research Analyst/Ontological Engineer

Laboratory for Bioimaging  & Anatomical Informatics
www.neuroterrain.org
Department of Neurobiology & Anatomy
Drexel University College of Medicine
2900 Queen Lane
Philadelphia, PA    19129
215 991 8430 (ph)
610 457 0443 (mobile)
215 843 9367 (fax)


Please Note: I now have a new email - William.Bug@DrexelMed.edu