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Multivariate Crosstalk Models

Authors: Natasha Young; Zheng Rong Yang;

Multivariate Crosstalk Models

Abstract

Since 1960s unexpected communication activity between signaling pathways and signaling molecules in cells has been very often observed. As there is no biological theory to interpret it, this activity has been termed as crosstalk, unwanted communication. So far, no computer or statistical models have been developed for modeling crosstalk between signaling proteins although studying crosstalk between signaling pathways in wet laboratory has been one of the main stream. As the first attempt in the world, we have investigated multivariate crosstalk models. The simulation shows that such statistical crosstalk models work very well although more investigations are needed.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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