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Finally, regarding the extracted relationship types as primary feature, feature similarity is calculated to measure the matching degree between their corresponding models.
In this article, we focus on extraction of the relationship between human motions and music pieces and perform the recommendation based on the extracted relationship.
For each relative included in the analyses, the following data were extracted: relationship to the index case; date of birth; vital status; age at interview or death; breast cancer status; and age at diagnosis, if affected.
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The extracted relationships are shown as a directed graph.
As noted, the extracted relationships represent not only direct regulation of expression by transcription factors, but also indirect relationships (e.g. "protein A regulates expression of protein B", and similar statements).
We found that precision increases with the recency and frequency of the extracted relationships.
The connectivity would, no doubt have been higher with the use of automatically extracted relationships from the biomedical literature.
The main issue of the hypothesis generation approach based on cooccurrence is that the extracted relationships lack logical explanations.
We noted that the extracted relationships are between larger or less specific brain regions than those in BAMS.
The latter were derived from almost 127 000 binary relationships, i.e. the complete events correspond to only 14% of the original extracted relationships.
By comparing with an independent source of rat connectivity, we found that precision increases with the recency and frequency of the extracted relationships.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com