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A MeSHOP is constructed by counting the number of times each medical subject term is assigned to an entity-related research publication in the MEDLINE database and calculating the significance of the count by comparing against the count of the term in a background set of publications.
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Second, the set of gene communities corresponds to a set of publication communities.
Our background set consists of 1000 sequences also from dbTSS.
Background set used was the entire set of known mouse genes.
However, FLAGS have more publications than the Background set (p-value = 6.3e−12).
The background set was defined as the drug sets of two dissimilar ADRs.
We used the entire set of core genes as our background set.
However these numbers have to be taken with care, because the background set corresponded to recent articles, while the PubMed database hosts a considerable number of older publications.
For academics, a background of publications relating to measurement properties of testing in exercise or sport (≥3 articles) was required.
Get your background set up.
The full set of journal publication titles and abstracts included in ChEMBL (47,939 documents in release 17) was the starting point, while a random but non-overlapping subset of the same size retrieved from MEDLINE [5] was used as the background.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com