Re: Experiment Ontology

Hi Bill,

Thanks for all of your great feedback. :-)

The folks at Lilly who developed the ontology did review a number of
existing ontologies, but they didn't meet our needs. I don't have the full
list of ontologies that they explored, but they definitely took a look at
OBI. We are very interested in working with the community to further
develop the ontology, and are in the process of scheduling a call with some
of the OBI folks.

Cheers,

Susie














                                                                           
             Bill Bug                                                      
             <wbug@ncmir.ucsd.                                             
             edu>                                                       To 
                                       Susie Stephens                      
             12/06/2007 11:16          <STEPHENS_SUSIE_M@LILLY.COM>        
             PM                                                         cc 
                                       Matthias Samwald <samwald@gmx.at>,  
                                       "public-semweb-lifesci@w3.org hcls" 
                                       <public-semweb-lifesci@w3.org>, Kei 
                                       Cheung <kei.cheung@yale.edu>,       
                                       "Karen (NIH/NIDA) [E] Skinner"      
                                       <kskinner@nida.nih.gov>, Alan       
                                       Ruttenberg                          
                                       <alanruttenberg@gmail.com>          
                                                                   Subject 
                                       Re: Experiment Ontology             
                                                                           
                                                                           
                                                                           
                                                                           
                                                                           
                                                                           




Hi Susie,

We certainly do need an "Experiment Ontology" - or Ontology of Biomedical
Investigation (OBI).

I believe Matthias, Michael, and Kei have all made exactly the points I
think are most important to consider:
1) Matthias's comments
Are you following "best practices" in creating the ontology.  I believe
Matthias gives many instructive examples on how to adjust what is here to
bring it much more in sync with the emerging "best practices" that are
coming out of the community development surrounding a variety of OBO
Foundry ontologies.  Matthias also makes the point that its important to
seek to re-use (or directly contribute to) the emerging community
ontologies to cover the required domains.  In the case of this particular
Experiment Ontology, the ontologies to consider are Ontology of Biomedical
Investigation (OBI), the OBO Relations Ontology, the Gene Ontology
(specifically the Molecular Function and Cellular Component branches, the
latter of which is designed to capture components down to the level of
macromolecular complexes), the Sequence Ontology, Protein Ontology (nascent
- but proceeding rapidly), the Cell Ontology - at a minimum.  As many on
this list know - and I'm certain the talented folks at Lilly who invested
time in assembling this ontology also learned - many of these are not fully
ready for prime-time, and/or may not FULLY cover the breadth and depth of
the domains a specific application requires.  However, if one doesn't seek
to work with these community efforts, you cannot expect to achieve the
ultimately goal, which is to make your data maximally "semantically
sticky", so as to ensure the least amount of custom logic and human effort
will be required to get the most value from your data.  Otherwise, you
stand the chance of creating what may be a useful ontology that meets your
specific requirements (as has been true of "investigation"-oriented
ontologies that have come before such as the MAGE Ontology, ExperiBase,
EXPO, myGRID KAVE, etc.), but don't help the community at-large to
appropriately re-use your data.  In each case, these ontologies or KR
frameworks have been extremely useful in the local application context for
which they were constructed, but they cannot be effectively employed as the
basis for semantically-driven integration across data sets that may not be
able to accept the constraints (or lack thereof) of this
application-oriented ontology.
Would you know off-hand, Susie, whether the folks who worked on this
ontology at Lilly have both reviewed the relevant community efforts cited
above and/or have sought to interact with those groups to get some input on
how best to meet the overall requirements that underlie this particular
Experiment Ontology with the minimal required effort and in a manner that
could help to ensure Lilly's sunk investment could be of benefit to us all.

2) Michael's comments
It's very helpful to know what the target is when it comes to
exporting/exchanging the actual data.  As Michael points out, a great deal
of work has gone into the production of FuGE (and MaGE before it) to come
up with the appropriate division of labor between the semantically-opaque,
syntactical requirements as represented in a data model such as MaGE or
FuGE and the explicit semantics as captured in the ontology.  For those
using FuGE, as Michael states, in the realm of syntax, the intention for
FuGE is to provide a shared structure for universal elements such as
biomaterials, experiment populations/pools/groups, protocol details,
reagents details, etc..  Built on that shared, generic foundation, any
specific discipline - e.g., microarray expression, GC-MS, FISH, MRI, etc. -
can sub-class FuGE components and add what additional detail required in
their discipline.  In parallel with this effort on data structure, the OBI
ontology cooperative seeks to provide that same foundation for the shared
semantic domains, and a clear set of recommended practices for how to
re-use entities from other OBO Foundry ontologies such as ChEBI, Sequence
Ontology, Protein Ontology, OBO Cell, Organism Taxonomy (OWL versions of
NCBI Tax), etc. to specify the critical biomedical entities and their
complex relations.  As I say above, these are works in progress.  For those
of us who must have something working now, the recommended practice is to
actively participate in these projects with an eye toward following their
practice - and replacing any "proxy" you create in the interim with the
community ontology, when it is ready for use.  This is what we have done in
the BIRN ontology BIRNLex.  We actually have an OWL module called
"BIRNLex-OBI-Proxy.owl" which we fully intend to replace with OBI entities,
when they are ready for use.  We also have "BIRNLex-Investigation.owl" that
builds on this "proxy" to cover entities BIRN researchers must capture.  We
expect to eventually see the contents of "BIRNLex-Investigation" in OBI in
some form.  We intend to "contribute" those elements from this OWL file
directly to OBI, when OBI is ready for them, and we have the time work
through this migration process.

3) Kei's comments
Examples - examples - examples.  This is critical.  Working through the
example Kei cites from the NIH Neuroscience Microarray Consortium is a
wonderful way to determine whether:
- there are existing community ontologies that can meet the KR and
processing requirements
- where the gaps are in those community ontologies
- whether the ontology you are creating effectively fills those gaps (if it
does, that makes it very clear how the community effort can make effective
use of your ontology)
In regards to Gene Lists, Kei is certainly correct.  If these are captured
through algorithmic means, it's critical to capture the details on that
algorithm - typically both the version of the algorithm as well as the
version of the data repository you ran it against.
Also - where gene entities are concerned - there is ongoing work between
the GO groups, the Sequence Ontology, and the Protein Ontology that is
particularly targeted toward capturing the specific relations between types
of genomic sequence elements and types of biologically active protein-based
molecules (e.g., macromolecular complexes composed of a collection of
proteins in a variety of post-translationally modified states - e.g., GPC
receptors, ion channels, transporters, pathway enzymes, etc. - i.e., Rx
drug targets).  These are the details we'll all require in order to do
round-trip pharmacogenetics - i.e.,effects of genetic constructs on
target susceptibility to drugs - AND - the ways in which drugs ultimately
alter macromolecular complexes by leading to changes in gene expression.

Just my $0.02 filtering on these helpful comments from Matthias, Michael,
and Kei.

Cheers,
Bill

On Dec 3, 2007, at 1:00 PM, Kei Cheung wrote:


      This is great!

      I have a microarray experiment description (that has to do with
      Alzheimer Disease) extracted from NINDS microarray consortium:

      http://arrayconsortium.tgen.org/np2/viewProject.do?action=viewProject&projectId=433773

      I just wonder how this example would fit this experiment ontology (as
      well as others such as OBI) As shown in this example, we record
      information such as organ type, organ region, cell type (layer II
      pyramidal neuron), etc. NINDS microarry consortium uses different
      array platforms (e.g., agilent, Affymetrix, and cDNA)  for different
      organisms so one may need to divide chips into groups corresponding
      to different platform types. Each group can then be further divided
      into subgroups corresponding to different organisms.

      We also would like to capture gene lists (not the raw gene lists but
      the ones (much shorter) that indicate what genes are over/under
      expressed under certain experimental conditions). Such gene lists
      would usually be extracted from the literature. Also the analysis
      package (including version) that was used to generate a gene list
      should be identified. One possible use of these gene lists is to
      compare them to identify genes are differentially expressed under the
      same/similar experimental condition across different microarray
      experiments. This would help identify true signals from noises.

      Hope it helps.

      Cheers,

      -Kei



      Matthias Samwald wrote:

            Hi Susie,

            Susie wrote:
                  It would be great if you could take a look at it and
                  provide comments. The
                  ontology is available at:
                  http://esw.w3.org/topic/HCLSIG_BioRDF_Subgroup/Tasks/Experiment_Ontology

            * Some of the entities/properties are missing a rdfs:label or
            have an empty label (a string with lenght 0).
            * Some of the entities could be taken from existing ontologies
            like OBI, RO or some of the OBO Foundry ontologies. This would
            save work and makes integration with other data sources and
            ontologies much easier. By the way, there seem to be several
            groups working on ontologies for mircoarray experiments, or are
            at least planning to do that. It would be great if these groups
            could work together.
            * The class 'Chip type' should be removed and be replaced by
            subclasses of 'chip', e.g., 'chip (human)', 'chip (mouse)' etc.
            * Some of the object properties appear like they are intended
            to be datatype properties (e.g., 'has proteome id').
            * Many of the datatype properties could be replaced with object
            properties, possibly referring to third party ontologies -- of
            course this would require a richer ontology and more work spent
            on creating mappings. 'has molecular function' could refer to
            entities from the gene ontology, 'has associated organ' could
            refer to an ontology about anatomy and so on.
            * Object properties and their ranges are quite redundant.
            Property 'has reagent' has range 'Reagent', property 'has
            treatment' has range'Treatment' and so on. Maybe the ontology
            could be designed in such a way that there are only some
            generic properties such as 'has part'. This would make the
            ontology much easier to maintain, query and understand in the
            long term.
            * It is unclear how 'Gene list' is intended to be used.
            * 'Hardware' and 'Software' should not be subclasses of
            'Protocol'.


            Many of the datatype properties in this ontology look very
            interesting and might provide requirements for other
            ontologies. It would be great if some of them could be
            described/commented in more detail so that we know more about
            the requirements that motivated the creation of these
            properties.

            I hope that was somewhat helpful.

            cheers,
            Matthias Samwald









William Bug, M.S., M.Phil.                                          email:
wbug@ncmir.ucsd.edu
Ontological Engineer (Programmer Analyst III) work: (610) 457-0443
Biomedical Informatics Research Network (BIRN)
and
National Center for Microscopy & Imaging Research (NCMIR)
Dept. of Neuroscience, School of Medicine
University of California, San Diego
9500 Gilman Drive
La Jolla, CA 92093

Please note my email has recently changed

Received on Tuesday, 11 December 2007 17:21:31 UTC