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Re: [ontolog-forum] Need suggestions developing cardiac disease/phenotyp

To: "[ontolog-forum]" <ontolog-forum@xxxxxxxxxxxxxxxx>
From: Jie Zheng <jiezheng@xxxxxxxxxxxxxx>
Date: Thu, 04 Nov 2010 10:45:59 -0400
Message-id: <4CD2C727.5060202@xxxxxxxxxxxxxx>
For all/most of biomedical related ontologies, you can go to:
http://bioportal.bioontology.org/ontologies    (01)

For the ontologies under OBO foundry, you can find them listed on the page:
http://obofoundry.org/    (02)

Jie    (03)

Zhuk, Yefim wrote:
> Mike and Barry,
>
> What are the places populated with multiple ontologies for convenient search?
>
> Thank you,
>
> Jeff (Yefim) Zhuk
>
> -----Original Message-----
> From: ontolog-forum-bounces@xxxxxxxxxxxxxxxx 
>[mailto:ontolog-forum-bounces@xxxxxxxxxxxxxxxx] On Behalf Of Barry Smith
> Sent: Thursday, November 04, 2010 10:29 AM
> To: [ontolog-forum] ; Pradeep Kumar S; [ontolog-forum]
> Subject: Re: [ontolog-forum] Need suggestions developing cardiac 
>disease/phenotype ontology
>
> Mike leaves out one important step:
>
> 0. Find out what already exists in the relevant domain, and use what 
> has already been created as far as possible.
>
> In this case the first places to look will include:
>
> 
><http://wiki.geneontology.org/index.php/Cardiovascular>http://wiki.geneontology.org/index.php/Cardiovascular
> 
>
>
> http://www.bioontology.org/wiki/index.php/PATO:Phenotypes_in_OWL
>
> BS
>
>
>
> At 10:08 AM 11/4/2010, Mike Bennett wrote:
>   
>> Hi Pradeep,
>>
>> Here's how I tend to look at creating an ontology. Assuming the 
>> ontology is intended as a conceptual model of the reality itself, 
>> and is not constrained by any specific application requirement (i.e. 
>> it's a model of the problem and not the solution), I would proceed as 
>follows:
>>
>> 1. Have a strict taxonomic hierarchy in which something sits below 
>> something else if it is a "kind" of that thing, that is it inherits 
>> all the facts defined for that thing above, and its parents and so on;
>>
>> 2. If there are multiple ways of classifying things in the problem 
>> domain, consider honoring all that are relevant (for example, a 
>> whale is both a Mammal and a MarineAnimal). However, you may wish to 
>> consider that while reality and therefore ontology support multiple 
>> inheritance, most of the applications that use this information will 
>> not. Having multiple taxonomies will enable you to develop (and map 
>> against) different applications which classify the diseases in 
>> different ways. So you should be able to achieve a taxonomy for any 
>> application that you need to deal with.
>>
>> 3. At the top of your hierarchy have what sort of "Thing" everything 
>> is, that is "DiseasePhenotype" I would imagine. If there is a 
>> separate way of classifying the diseases (genotype?) then put a 
>> separate top level term, with an even more general term above that 
>> (e.g. Disease).
>>
>> 4. Finally the facts (properties). For every new kind of thing 
>> (every disease) ask yourself two questions:
>>
>>  - what sort of thing is it? (this determines where it goes in the 
>> taxonomy e.g. is it a neurone related or muscle related condition);
>>  - what facts distinguish it from other things in that part of the taxonomy?
>>
>> This latter gives you the necessary facts that define that that 
>> thing is what it is.
>>
>> There may be other, incidental facts. In financial securities we 
>> have lots of facts that always apply to a given kind of security so 
>> it's not always obvious which one is a necessary, defining fact. For 
>> example exchange traded options are distinguished by the fact that 
>> they are traded on an exchange, and also by the fact that they have 
>> specific, standardized legal terms. So don't worry too much about 
>> distinguishing necessary from incidental facts since the main 
>> semantics notations don't have a means to put that in anyway. Just 
>> make sure you have captured the necessary facts that give a thing its 
>meaning.
>>
>> If no facts distinguish something from something else, you have a 
>> synonym (at least at the level of detail you have considered 
>> appropriate for this particular ontology). Rather than have separate 
>> classes for each word or disease name that exists, you should 
>> consider having one class for each meaning, and then identify 
>> synonymous words in a separate "synonym" tag. Unfortunately there 
>> isn't a synonym tag in OWL (people seem happy to have a class per 
>> word and use equivalence relations, which is unnecessary and I would 
>> suggest counter productive). So either use RDFS Label or find some 
>> way of identifying particular RDFS Labels as "synonym". Here you 
>> might also want to have separate synonym tags with a language 
>> marker, so you have all your Latin terms.
>>
>> Ultimately the questions of what amount of relationships / facts to 
>> put in, is a judgement call based on what level of detail of terms 
>> you need in any applications you will develop from this ontology, or 
>> what level of detail exists in databases, data feeds and 
>> applications that you wish to relate to with this ontology, for 
>> example if you are using it for integration of disparate systems or 
>> to create a common messaging language.
>>
>> What I found is that once you get an initial draft in place and 
>> present this to the business subject matter experts to review (I 
>> hope you will be doing this, since it's their knowledge), they will 
>> tend to let you know about additional facts and levels of detail 
>> that are relevant to a given application or to their view of the 
>> business domain. For example when we looked at legal entities, we 
>> had 4 terms for kinds of relationships among entities, but the 
>> business experts identified up to 4 possible shades of meaning for 
>> each of these, that they considered relevant, for instance for 
>> different levels of control and different kinds of control that one 
>> legal entity has over another.
>>
>> So once you have got your ontology into the hands of the business 
>> domain experts they will pretty much fine tune the level of detail 
>> for you. The key is making sure that it is structured, and can be 
>> presented and explained, in simple set theory logic with the 
>> necessary defining facts in place.
>>
>> Hope this helps,
>>
>>
>> Mike Bennett
>>
>>
>> On 04/11/2010 13:38, Pradeep Kumar S wrote:
>>     
>>> Dear all,
>>>
>>> I hope this is the right place to request for some help I need 
>>> developing a cardiac disease/phenotype ontology.
>>>
>>>
>>> I have been curating list of phenotype/disease terms from 
>>> biomedical literatures for past 1year.
>>> Now the collection has grown to about  ~1200 terms. I have the 
>>> following attributes curated along with the terms:
>>> 1. Term name
>>> 2. Source ( web, reference of book or paper)
>>> 3. Some times definition and the context in which it was curated.
>>>
>>>
>>> I request experts here to suggest me how to proceed further from 
>>> list of terms to making a good ontology?
>>>
>>> Specifically I need to know:
>>>
>>> 1.     how many relationships should I consider initially. Putting 
>>> terms under hierarchy like a taxonomy will be the easiest. But how 
>>> to incorporate other plausible relationships. When (how many) would 
>>> it get very complex?
>>>
>>> 2.     Basically I want to render a ontology that could be used by 
>>> data mining tools and serve biological community in their data analysis.
>>>
>>>
>>>
>>> Any suggestions from experts here will be highly appreciated.  Also 
>>> please point me to any websites/literature/books that would be of help.
>>>
>>>
>>>
>>> Thanking you,
>>>
>>> --Pradeep
>>>
>>>
>>>
>>>
>>>
>>>
>>>
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>>>       
>>
>> --
>> Mike Bennett
>> Director
>> Hypercube Ltd.
>> 89 Worship Street
>> London EC2A 2BF
>> Tel: +44 (0) 20 7917 9522
>> Mob: +44 (0) 7721 420 730
>> <http://www.hypercube.co.uk>www.hypercube.co.uk
>> Registered in England and Wales No. 2461068
>>
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