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Confirmed evidence for linkage at the 6p22.3 locus was followed up with allelic association studies using the family based methods implemented in TRANSMIT [ 11].

Table  1 also illustrates that RP-based methods implementing a secondary SR-mapping step can perform very well in deep-sequencing data because such high-coverage datasets likely contain RPs that map across the breakpoints and additional reads that can be SR-mapped across the breakpoint for fine localization.

Ancestral distributions were estimated on the Bayesian consensus phylogram under Maximum Parsimony using MacClade v4.0 [ 66] and under a dispersal-vicariance event based method implemented in DIVA 1.1 [ 83].

We also used a two-step semantic similarity based method implemented by R package csbl.go [ 51].

Therefore, we used a more powerful maximum-likelihood based method, implemented in the CodeML subroutine of the software PAML [ 63] which allows the rates of ω = dN /dS to vary among codons [ 31, 64].

The maximum likelihood based method implemented in the codeml program of the PAML package (v3.15) [ 38] was used to detect positive selection as well as identifying positively selected sites, when the number of related sequences was sufficiently high.

In the present study, three methods were used: a distance-based method called ParaFit implemented in CopyCat [ 80] and topology (or tree -based metree -basedmethodsimplementednd TreeMap 3 (developed by Mine Charleston and available at http://sites.google.com/site/cophylogeny).

All of these machine learning based methods are implemented by using WEKA software package with default parameters setting and carried out 10-fold cross-validation based on topological features and biological features mentioned in section Method.

The phylogeny was constructed using a maximum likelihood based method as implemented in PhyML [ 72] using the JTT substitution model [ 73] with the default proportion of invariable sites (0.0) and rate heterogeneity between sites corrected by a gamma law (using the default gamma parameter of 1.0 and eight rate categories).

Fat volume quantification plays an important role in the research of obesity induced diseases; this paper will focus on a reliable fat separation method utilizing a typical NMR sequence as opposed to a more exotic chemical shift based methods not yet implemented at high field strengths in small animal imaging in this case specifically at 7T.

In a related context, an abstraction for the solution of partial differential equations with grid based methods has recently been implemented in the (Py OP2 library.