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[Fwd: Re: bibliography of GO usage?]

Judith Blake jblake at
Wed May 18 13:26:54 PDT 2005

Hi Bill,

Thanks for these comments.  As has been noted, the bibliography on the
GO pages is extensive, but we can do more and are working on that now.
The publications listed now are sorted by

Publications on GO by members of the GO Consortium
Annotations using GO
GO in gene expression studies
Prediction of GO annotations
GO Tools
Other publications with substantive discussion of GO
Publications on other OBO ontologies

These have been collected as systematically as we can primarily by
queries of PubMed abstracts for 'Gene Ontology', or by gleaning and
submission by interested parties. What we systematically miss are those
papers where 'gene ontology' or "GO" (even harder) are referred to in
the full text, but not the abstract.  We are now working with some full 
text searching options that will allow better representation of these
papers.  Often, these are the papers that reflect the work of the
experimental biologist who uses GO in the analysis, but would not put
'gene ontology' in the abstract.  These would be the ones you are 
referring to below.

I am curious as to how you (others) would like to query the
bibliography.  Would it be by experimental assay (microarray analysis,
function prediction, etc.) in addition to standard queries by auther,
journal etc.??  Thanks for any input.

In a more general coment, I think an important consideration for the
experimental biologist is that their experimental work can be evaluated
within the context of other experimental data that may have been
annotated at different levels of granularity only if both data sets are
aligned to a some standard...and ontologies bring even greater power
to the analysis.

Thanks for your input.


William Bug wrote:

> Dear GO folks,
> I was wondering whether their is a list somewhere of published 
> articles containing significant scientific questions specifically 
> answered via the use of GO?
> I realize use of GO in genomics and gene expression studies has become 
> so ubiquitous over the past 5 years it may seem a bit ludicrous to 
> even try to compile such a list.
> However, in the informatics work I - and many others - do lying 
> outside the mainstream of genomics/transcriptomics, I find myself 
> often having to evangelize on the topic of why it's so crucial to use 
> ontologies/controlled vocabularies where ever practical.  Since I'm 
> generally in the role of providing informatics infrastructure, when 
> asked by an scientific investigator to justify the extra up-front work 
> required to use ontologies when managing scientific data, my first 
> inclination is to say:
>     "If your data is not placed in this formal, systematized context, 
> it will be very costly - maybe prohibitively so - to both integrate it 
> with other, external related data sets and to provide a means to 
> either search or statistically analyze the body of data as a whole 
> without resulting in many false negatives - missing data records 
> because they were not tagged with deterministic, semantically-relevant 
> labels.  If the systems we build to house & manipulate your data are 
> not onto-centric (or eschew use of formalized data standards, for that 
> matter), it may also be prohibitively expensive to enable those 
> systems as a whole to interoperate with related systems providing 
> complementary data and services."
> Those can be a rather opaque arguments and not particularly compelling 
> to a biological scientist.  The true cost of that cautionary argument 
> often is not recognized until later, when you try to build such 
> search/browse/stats reduction systems.  By then, the cost of 
> introducing onto-centric data management practices is much greater, 
> than if you do it properly from the outset.
> So - I started through the course of my reading to compile a 
> bibliography of the sort of examples I describe in the first sentence 
> above - compelling exemplars of GO's use to directly answer scientific 
> questions.  For example, in this article from last October's 'Genes In 
> Action' issue of 'Science' ("A Gene Expression Map for the Euchromatic 
> Genome of Drosophila melanogaster", 'Science', v306, n5696, p655, 
> 2004.), they state on the 2nd pg, 1st col, 2 para:
> "We noted that mRNA expression levels for protein-encoding genes 
> varied with the protein function assigned in the Drosophila Gene 
> Ontology. For example, genes encoding G protein receptors were 
> expressed at relatively low levels, whereas genes encoding ribosomal 
> proteins were highly expressed.  A gene^Òs expression level was also 
> associated with cellular compartmentalization and the biological 
> process it mediates."
> I think that is a simple, cogent and compelling example of how 
> critical use of GO can be to - in this case - genome-wide - expression 
> analysis.
> Then I thought, "wait a minute, the GO Consortium or one of the heavy 
> users of GO has probably already pulled together such a bibliography.  
> They would be considerably more qualified than I to decide which 
> references should be on such a list anyway."
> I'm pretty certain the NLM actually compiles such a list for UMLS (the 
> Unified Medical Language System).  To use UMLS, you must acquire a 
> license from NLM, which obligates you to report back to NLM on a 
> yearly basis what research you have done using UMLS.
> I went to the GO web site - a beautiful portal, extremely well 
> organized, all the tools & resources you need to effectively implement 
> a project using GO - all with a well-designed esthetic (pardon the 
> editorializing).  There is a thorough, current bibliography of GO 
> research - "Publications on GO by members of the GO Consortium" which 
> I've used myself a lot, but this isn't really what I need.
> That is why I'm posting this request here.
> Has anyone compiled a bibliographic reference list on GO usage?  I 
> realize again this may seem absurd given how wide-spread use of GO has 
> become in bio-molecular informatics.  However, I know being able to 
> point people to such a list would be of great value to the work I do.  
> It would be even better if such a list were to reside in an 
> onto-centric bibliographic database and could be served up dynamically 
> via a web site, where an investigator could query for GO usage in 
> their field of study.
> Many thanks for bearing with me to the end of this message and thanks 
> too for any assistance you can provide on this issue.
> Cheers,
> Bill Bug
> Bill Bug
> Senior Analyst/Ontological Engineer
> Laboratory for Bioimaging  & Anatomical Informatics
> Department of Neurobiology & Anatomy
> Drexel University College of Medicine
> 2900 Queen Lane
> Philadelphia, PA    19129
> 215 991 8430 (ph)
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