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We used the FatiGO functional analysis tool [ 66] to explore the relationship between biological function and homoeologous gene expression patterns.
This type of approach brings robust information about the relationship between biological function and physiological changes.
This correlation between biological function and expression pattern suggests that machine learning algorithms could be successfully applied to predict function from expression data [ 16– 20].
The objective of this study is to empirically examine the relationship between biological function and the rate of sequence divergence after a duplication event.
A hierarchy of groupings can emerge using this methodology, and such analyses have previously shown relationships between biological function and anatomical location (Gerstein and Jansen 2000).
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Thus, no striking relationship between biological functions and oyster capacity to survive infections was clearly evidenced.
Koike et al. (2004) reported work on finding relations between biological functions and genes and gene products.
The authors showed that a strong correlation between biological functions and expression profiles led to a cluster.
To examine the association between biological functions and the NIMS predicited synergy, we used permutation tests and SRCC to evaluate whether the genes related to the synergistic agent pairs predicted by NIMS tended to have co-annotations in GO [ 61].
The paper titled "Development and Mining of a Volatile Organic Compound Database" discusses creation of a new VOC database by collecting information scattered in scientific literature and analyzed the accumulated data to show relations between biological functions and chemical structures of VOCs.
A rich source for testing the relationship between biological function, gene duplication and intraspecific genetic variation are databases describing the metabolic pathways known and predicted within a host of organisms [20], [21].
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