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I'm inclined to agree with Chris.

My thinking is that, if a particular software package was interested in supporting mean, sd, ranges, it is quite likely that it would either already be supporting the distrib extension or would be doing so in future. distrib seems a suitable home for this.

Cheers,

Neil.

Neil Swainston, PhD
Research Fellow

Manchester Institute of Biotechnology
University of Manchester
Manchester M1 7DN
United Kingdom

On 12 Jul 2012, at 19:40, "Chris J. Myers" <myers@ece.utah.edu> wrote:

> My preference would likely be (2), in the distrib package. I don't
> think the argument against it is significant over (3) as if you make a
> new package than you would need to understand that one. I think a
> nice way to do this would be to introduce an "unknown" distribution
> with four parameters in the same way we discussed introducing other
> distributions. This could then take four parameters, those you list.
>
> Chris
>
> On Jul 12, 2012, at 9:32 AM, Nicolas Le Novère wrote:
>
>> Hello,
>>
>> The wish has been expressed for a long time to be able to encode
>> uncertain
>> values in SBML models. One particular need is for population models,
>> and
>> this will be cater for by the "distrib" package. This package will
>> allow to
>> define and sample from "distributions" of values, either using
>> mathematical
>> functions, or list of numbers. There is another situation, where we
>> just
>> want to store uncertain values. For instance because this is how it
>> was
>> reported in the literature and we use SBML as a mean to store
>> knowledge
>> about biochemical pathways. Or because we want to use the SBML file
>> as an
>> intermediate in a workflow, the final values being determine at a
>> later
>> stage.
>>
>> We need to be able to encode at lease 4 information:
>>
>> * the arithmetic mean
>> * the standard deviation
>> * a lower value
>> * an upper value
>>
>> This information of course is mostly a form of annotation. If you do
>> not
>> know the distribution of the value, you cannot do much in terms of
>> mathematical interpretation of the model. And if the distribution is
>> available, then the distrib package should be used. So the role of the
>> corresponding structures would be rather like the "reversible"
>> attribute on
>> the reaction element.
>>
>> After playing with the idea of using regular distributions in the
>> distrib
>> package, with things like "first moment" for the mean and "second
>> moment"
>> for the stddev, it seems - after discussions at HARMONY2012 - that the
>> easiest way would rather to just add three optional attributes to any
>> element carrying a value (the value being identical to the mean if the
>> attribute stdev is defined).
>>
>> The big question is the package to which those attribute should
>> belong to:
>> 1) core (remember those are optional attributes)?
>> 2) distrib?
>> 3) another package? (at some point it was suggested to develop a stat
>> package, for instance to extend the MathML).
>>
>> All solutions have their appeal, and all solutions have their
>> drawbacks.
>>
>> 1) is harder to implement due to the stiffness of the core, and the
>> perception that the burden will be high on all shoulders.
>> 2) will tie the attributes to distrib, and therefore they will only be
>> accessible to tools understanding distrib.
>> 3) will force the creation of a new package, with all the management
>> hassle, but would make easier future independent evolutions (i.e.
>> adding
>> median).
>>
>> Opinions? Ideas?
>>
>> --
>> Nicolas LE NOVERE, Computational Systems Neurobiology, EMBL-EBI, WTGC,
>> Hinxton CB101SD UK, Mob:+447833147074, Tel:+441223494521 Fax:468,
>> lenov@ebi.ac.uk, Skype:n.lenovere, twitter:@lenovere
>> http://www.ebi.ac.uk/~lenov/, http://www.ebi.ac.uk/compneur/
>>
>>
>>
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