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==Summary== | |||
{{Information | |||
|Description='''Figure 4.''' Prevalence of several gene ontology terms that could be associated with the top rules. The importance of regulatory mechanisms becomes immediately clear when looking at the most frequent terms. The top term has a support value of 808 (GO:0005524) refers to ATP-binding functions, while the second directly names protein phosphorylation (GO:0006468) as the underlying mechanism of this figure. The other terms, such as GO:0004674 (protein serine/threonine kinase activity), GO:0004672 (protein kinase activity), and GO:0018108 (peptidyl-tyrosine activity) only further strengthen this observation. Overall, we can conclude that in the human interactome dataset, interactions with kinases seem to be the most prevalent, with kinases co-occurring with an extremely diverse amount of substrate domains. However, the most specific substrate domains are only found at lower support values. | |||
|Source={{cite journal |title=Practical approaches for mining frequent patterns in molecular datasets |journal=Bioinformatics and Biology Insights |author=Naulaerts, S.; Moens, S.; Engelen, K.; Vanden Berghe, W.; Goethals, B.; Laukens, K.; Meysman, P. |volume=10 |pages=37–47 |year=2016 |doi=10.4137/BBI.S38419 |pmid=27168722 |pmc=PMC4856181}} | |||
|Author=Naulaerts, S.; Moens, S.; Engelen, K.; Vanden Berghe, W.; Goethals, B.; Laukens, K.; Meysman, P. | |||
|Date=2016 | |||
|Permission=[https://creativecommons.org/licenses/by/3.0/ Creative Commons Attribution 3.0 Unported] | |||
}} | |||
== Licensing == | == Licensing == | ||
{{cc-by-3.0}} | {{cc-by-3.0}} |
Latest revision as of 18:46, 24 August 2016
Summary
Description |
Figure 4. Prevalence of several gene ontology terms that could be associated with the top rules. The importance of regulatory mechanisms becomes immediately clear when looking at the most frequent terms. The top term has a support value of 808 (GO:0005524) refers to ATP-binding functions, while the second directly names protein phosphorylation (GO:0006468) as the underlying mechanism of this figure. The other terms, such as GO:0004674 (protein serine/threonine kinase activity), GO:0004672 (protein kinase activity), and GO:0018108 (peptidyl-tyrosine activity) only further strengthen this observation. Overall, we can conclude that in the human interactome dataset, interactions with kinases seem to be the most prevalent, with kinases co-occurring with an extremely diverse amount of substrate domains. However, the most specific substrate domains are only found at lower support values. |
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Source |
Naulaerts, S.; Moens, S.; Engelen, K.; Vanden Berghe, W.; Goethals, B.; Laukens, K.; Meysman, P. (2016). "Practical approaches for mining frequent patterns in molecular datasets". Bioinformatics and Biology Insights 10: 37–47. doi:10.4137/BBI.S38419. PMC PMC4856181. PMID 27168722. http://www.pubmedcentral.nih.gov/articlerender.fcgi?tool=pmcentrez&artid=PMC4856181. |
Date |
2016 |
Author |
Naulaerts, S.; Moens, S.; Engelen, K.; Vanden Berghe, W.; Goethals, B.; Laukens, K.; Meysman, P. |
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