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It allows for the identification of interactions between design variables.
An increasing number of neuroimaging studies are concerned with the identification of interactions or statistical dependencies between brain areas.
Biochemical evidence aids in the identification of interactions between genes and proteins, but the spatiotemporal dynamics of these interactions are more difficult to probe using conventional techniques.
In contrast, the traditional Cox regression approach has some drawbacks in the sense that it does not allow for the identification of interactions between genomic features, which could have key roles associated with cancer prognosis.
In this article, a systematic approach for the automatic detection of feature interactions in embedded control systems is presented, which allows the identification of interactions within a system as well as the detection of interactions that are caused by the environment.
The traditional approach to studying complex biological networks is based on the identification of interactions between internal components of signaling or metabolic pathways.
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In this study the main criteria for the identification of interaction with users is the mention of consumer, user, or any activity which requires a person.
Since we expect major advances in mapping protein metabolite interactions in the near future, the challenge shifts to the identification of interaction functionality, for which currently only few specialized methods are available.
We have shown this approach to be successful in the identification of interaction pathways and conserved regions in a diverse set of protein-ligand systems.
As this could possibly involve the DD of MALT1 and/or the CARD (caspase recruitment domain) of API2, the identification of interaction partners for these domains would form the subject of interesting future research.
Another application of the scoring function is the identification of interaction partners for orphan SK and RR proteins, i.e., SK or RR genes, which are located in isolation in the genome and consequently do not have easily identifiable interaction partners.
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