[Ontology-editors] small molecule metabolism

[Harold Drabkin]

arrgh! Alex reminded me of sucrose and lactose.
maybe we want to cut it off above 2?

There goes my epiphany!

h


Harold Drabkin wrote:
> a thought..
>
> How about saying that these are the non-polymeric molecules found 
> within a cell? (assuming we do not want to count di-peptides, 
> di-nucleotides, or di-saccharides )?
>
> hd
>
> Chris Mungall wrote:
>>
>> On Apr 9, 2009, at 9:35 AM, Valerie Wood wrote:
>>
>>> Tanya Berardini wrote:
>>>
>>>>
>>>>
>>>> On Thu, Apr 9, 2009 at 8:48 AM, Chris Mungall <cjm at berkeleybop.org 
>>>> <mailto:cjm at berkeleybop.org>> wrote:
>>>>
>>>>
>>>>    On Apr 9, 2009, at 3:35 AM, Valerie Wood wrote:
>>>>
>>>>        It seems like there is a gap in the terminology of biology to
>>>>        decribe "everything that is not a macromolecule molecule".
>>>>        Maybe we should make one up....
>>>>        Perhaps "small molecule metabolism" would be acceptable if it
>>>>        is defined as "everything that is not a macromolucule" but
>>>>        that is not an acceptable way of defining something is it?
>>>>
>>>>
>>>>    Do we really need a term for it? Why not just ask for non-X
>>>>    metabolism any time you're interested in metabolism of Ys where Ys
>>>>    are not Xs
>>>>
>>>>    Granted tools can't do this yet but it's not hard given the
>>>>    correct structures in the ontology, and we should perhaps be
>>>>    working towards a situation where tools do support this
>>>>
>>>>
>>>> I am partial to this approach.  Defining 'small molecule 
>>>> metabolism' as everything that is not 'macromolecule metabolism' 
>>>> violates the ontology design principle of positivity.  Why not just 
>>>> combine the annotations from the terms that do cover what is 
>>>> desired and then analyze those results?
>>>>
>>>> Tanya
>>>>
>>>
>>> Its quite difficult  to do this during enrichment analysis.
>>> I have seen  a number of times that   terms which would be 
>>> classically termed "biochemical pathways" are enriched, bacause I 
>>> see the annotations  in my data individually.
>>> The enrichment tools don't show this  because the number of 
>>> annotations to the individual  terms are not large enough. tThe 
>>> parent term "cellular metabolic process" is not enriched because the 
>>> effect is masked  by all of the other 3000 annotations to this term 
>>> generated  mainly by the variouse types of macromolecule metabolic 
>>> process i.e.DNA metabolic process, protein metabolic process etc.
>>>
>>> When you are analysisng whole genome datasets it isn't really 
>>> practical to add and subtract processes and repeat enrichment (it 
>>> gets way too complicated to process and report the results, as you 
>>> would have to fiddle with the P-values for everything you did 
>>> manually and then reintegrate it into your whole genome analysis)
>>>
>>> This isn't really a problem for me now because I worked around it, 
>>> but I could only do this because I know what the problem was.
>>>
>>> I thought that other users may appreciate some sort of grouping term 
>>> here for similar analyses- it just seems that there should be a term 
>>> to group these processes in the same way that macromolecular 
>>> metabolic processes are grouped. The fact is that if you have a 
>>> bunch of genes enriched for low numbers of  various small 
>>> metabolism/canonical biochemical pathway terms, this  enrichment 
>>> would  most likely be overlooked.
>>
>> I agree with Tanya but understand the practical need for enrichment 
>> analysis.
>>
>> I am envisioning a partial solution along the following lines:
>>
>> Just as we have goslims, we can have gofats. a gofat would live 
>> outside the ontology and contain statements like
>>
>> GOFAT:1 small molecule metabolism = metabolism and not 
>> has_participant chebi:macromolecule
>>
>> The reasoner would compute is_a parentage to the fat terms and create 
>> a derived obo file. If the tool accepts OBOFs+GAFs then just give the 
>> tool this obo file instead of the regular one.
>>
>> (note this only works for tools that allow you to input an obo file. 
>> Some web-based tools may not give you the flexibility to substitute 
>> anything other than the regular GO)
>>
>> This should work in your particular case, no need to keep 
>> re-analyzing once you've defined your fat. We could even make the 
>> fat-derived obo files available on the website, as we do for slims
>>
>> This solution isn't perfect as it requires the analyzer to know a 
>> priori which may be useful grouping categories. Really the tool 
>> should be able to do this. For example, for a particular dataset, 
>> "metabolism with a molecule with an X side chain, missing a Y" may be 
>> enriched. There are strategies for dealing with this - rule mining, 
>> or pre-computing every possible cross-product. This will require a 
>> little more know-how from tools developers.
>>
>>
>>>
>>> val
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>>
>>> -- 
>>> The Wellcome Trust Sanger Institute is operated by Genome Research 
>>> Limited, a charity registered in England with number 1021457 and a 
>>> company registered in England with number 2742969, whose registered 
>>> office is 215 Euston Road, London, NW1 2BE.
>>
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