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we compared CARROT with two existing methods for relationship inference, RELPAIR (Epstein et al., 2000) and PREST-plus (McPeek and Sun, 2000; Sun et al., 2002).
Current methods for relationship inference consider only a small set of close relationships and have limited to no power to distinguish between relationships with the same number of meioses separating the individuals under consideration (e.g. aunt niece versus niece aunt or first cousins versus great aunt niece).
Existing methods for relationship inference (Epstein et al., 2000; McPeek and Sun, 2000; Sun et al., 2002) use HMMs to compute the likelihood of the observed genotypes under a set of alternative relationships and then select the relationship that maximizes that likelihood.
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To solve the above issues, the traditional methods for inferring relationship are by performing a statistical similarity analysis of time sequence from dynamic elements.
We also intend to further develop methods for investigating relationships between candidate genes/proteins.
This review introduces methods for investigating relationships between two qualitative (categorical) variables.
Although published studies have described methods for assessing relationships between disease diagnostic categories in a network context [ 6, 29], we instead focused on multiple disease-related phenotypes within one complex disease.
All three methods accounted for relationships either through pedigree or genome-wide markers.
dnet implements two methods for characterising sample relationships (here relationships across tumour types): one is to build a neighbour-joining tree, the other is to create a self-organising landscape.
And they'll be announcing a fifth shortly – No. 7,478,078, titled "Method for sharing relationship information stored in a social network database with third party databases".
Saric et al. focused on detecting the noun phrase (NP) of biological entities that use the active and passive voices and proposed the NLP based method for regulatory relationship extraction [17], [18].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com