Dear Mr Perret,

An important question related to the quality of your database is how it is structured? Is it related to an existing ontology?

Cheers

Unfortunately , no. It s a classical bibiography data base like end note.

Might be useful for basic research to guide readers outside the field regarding initals or synonyms for long named enzymes etc.

Ontology methods and Symantec web supporting languages .RDF format and SWRL ...

dear johannes

I don't know but as it is possible to export the files to end note , I think it is under the xml format . My problem is that the synonym list , and more importantly the link between this list and the files, is not exported to end note.If you had a solution, i would be glad.

May I refer to UMLS which has a thesaurus of many tens of thousands of terms, their synonyms and commonly used identifiers in many ontologies?

UMLS doesn't suit very well to the daily practice of biomedical researchers who are not very easy with the hierarchical structure of MESH. They prefer generally to use the keywords given by the authors or created by themselves after the reading of the article.

The list I propose is founded on this principle.

Gerard, I LOVE your enthusiasm, but I agree with the subtext of some of the comments here: is the quality of the data worth your effort of trying to do this project?

The reason why I weigh in is that I was a HUGE user of EndNote from about 2000 to 2012, when I abandoned it for Zotero, which I now highly recommend (www.zotero.org). To populate my EndNote library, I'd connect to PubMed and import the reference. I noticed when I collaborated with other EndNote users, if they had populated their libraries a different way (e.g., manually, connecting to a different source, etc.), if we merged our EndNote databases, our records would essentially come in as two, distinct, unique records - even though they had the same ISBN numbers, for example. That's the way the database goes! Then we had a lot of clean-up to do - another reason why I eventually moved to Zotero, which is more comfortable with a multi-user environment.

I'm not sure what connections you'd want to make in terms of synonyms, but I also want to add that when journals ask us authors to provide "keywords", most of us don't do a very good job, and no one stops us. For example, I'm pulling some articles on child abuse; some are tagged "child abuse", some "human", and some "English", but many are missing those tags that actually have those attributes. I have to retag everything according to my own ontology in my citation programs (another thing Zotero makes easier than EndNote, IMHO).

You might just want to eyeball the data and see how consistent the dataset is, the way I just eyeballed my "child abuse" library. I'm imagining using the PubMed database (the "horses mouth"), and you'd still have the tagging problem I expressed above.

I still think what you have is a very good idea, but the data may just not cooperate. If you go forth, let us know how it goes!

-Monika

Monika, thank you for your kind remarks.Johannes is right . My main purpose is to vonvert an old fashioned and obsolete database ( Bibliomac) in a more modern but in keeping the main functoinnality of bibliomac: the ability ro link a bibliographic reference to a group of synonyms. End note is not able to do it. Would be Zotero ?

UMLS and MESH ontology is very good to manage synonyms of simplesemantic entities ( for example: adrenoceptors/adrenergic receptors) but is less efficient for complex query : for example VEGF expression /production/ secretion by cancers/tumors or Effects of thyroid hormones on heart. The use of the boolean operator AND does not work always because it catch up the different terms without respecting the hierarchy of the sentence (of, in,by,) and broadening too much the research ( for example cancer, cancer cells, cancer cell lines). The use of the entire sentence and its synonyms avoid this .It's the main reason , I think, my list could be useful if the link with the references is kept on.The second reason is that these descriptors have been made after a reading of the full text of the article and can't be deduced from the title , the abstract or the author's key words.Ideally, It could be the first step to build a knowledge database with the help of a network of biomedical researchers ( following the model of the protein-protein interaction of the Van Buren Lab). What do you think about this possibility ?

thank you very much. I sent you the material.

Have a nice week end