Sentence examples for amalgamation algorithm from inspiring English sources

TERA's amalgamation algorithm can be regarded as a generalization of the gene tree reconciliation algorithm of Doyon et al.

To circumvent this problem, David and Alm (2010) introduced the amalgamation algorithm, described in detail in Section 2.3 below and illustrated in Figure 1.

Finally, we used a recursive partition and amalgamation algorithm to identify patients at intermediate and high mortality risk (hazard ratio 7.0 and 24.4, respectively, as compared with those at low risk).

The amalgamation algorithm itself is a joint dynamic programming recursion over (i) all trees that can be produced from clades present in the input sample and (ii) all possible ways to reconcile each of these trees with the species tree, to recover a gene tree with the smallest joint sequence-reconciliation score.

A collection of large trees obtained through such stochastic amalgamations would account for the effect of finite sample sizes (sequence length) as well as the sensitivity of the amalgamating algorithm itself to variation in the input vector of small tree estimates.

Furthermore, the recursive partitioning and amalgamation (RECPAM) algorithm (16, 17) was used to identify subgroups of patients at different mortality risks according to the mortality risk score.

A tree-growing technique, based on the RECursive Partitioning and AMalgamation (RECPAM) algorithm, 26 was used to investigate possible interactions among demographic and clinical variables in order to identify distinct and homogeneous patient subgroups in terms of EI.

Here we present the TERA algorithm (Tree Estimation using Reconciliation and Amalgamation) that amalgamates the most parsimonious reconciled gene tree from a set of gene trees reconstructed from a unique gene alignment, according to a joint sequence-reconciliation score.

Therefore a novel control algorithm, which is an amalgamation of fractional mathematics and IMC-PID, having less design parameters is proposed.

Our algorithm is based on dynamic amalgamation of objects (for example, expression profiles) in vicinity of an artificially introduced object (FORmal ELement).

The self-consistent score estimation scheme used by TERA, introduced in Section 2.4, should be applicable to other parsimony methods, while amalgamation is in theory compatible with any reconciliation algorithm that assumes branches of the gene tree to be independent.