Sentence examples for most informative common from inspiring English sources

In the earlier developed measures, the similarity of two GO terms is defined as the information content of their most informative common ancestor (MICA), indicating its specificity.

In this case, the similarity between these two terms is proportional to the information content of the most informative common ancestor between them.

Briefly, the semantic similarity of two GO terms is first defined as the information content of their most informative common ancestor.

The earliest proposal on the IC-based approaches was suggested by Lord et al. [ 8], who used Resnik's metric [ 9] to quantify semantic similarity between terms in the GO DAG, which is the information content of the most informative common ancestor (MICA) of these terms; that is, the similarity between two terms is simply the information content of the most specific parent of these terms.

Given two concepts c 1 and c 2, their shared information, Share (c 1, c 2 ), can be defined as the information content of their most informative common ancestor (CommonAnc(c 1,c 2 )) [ 28]: (8) S h a r e (c 1, c 2 ) = m a x { I C (a ) | a ∈ C o m m o n A n c (c 1, c 2 ) } The most common semantic similarity measures are Resnik [ 29], Lin[ 30] and Jiang [ 31].

Given a hierarchical ontology structure, this can be quantified thus: (1) Sim (a,  b ) = IC MICA a, b) max{IC a , IC b } where ICMICA a,b) is the information content (IC) of the most informative common ancestor (MICA) of the terms a and b.

As the most informative RMGs reflect common CNA's or regions of epigenetic silencing, we suggest that these genomic modifications act co-operatively and additively to produce cancers with higher proliferative capacity.

Because orthologs are most informative when they share a common overall domain architecture [20], we gathered homologs from the UniProt database and constructed a phylogenetic tree for an evolutionarily conserved region (residues 58 to 263) spanning the predicted FMN-binding split barrel domain and most of the DUF2470 domain (Figure S1).

The critical factor in the transfer of learning effects between tasks is not the task or stimulus arrangement, but rather the recruitment of common sets of neurons most informative for making each perceptual judgment.

The critical factor underlying the transfer of learning effects is not the task or stimulus arrangements themselves, but rather the recruitment of commons sets of neurons most informative for making each perceptual judgment.

The interspecific genetic linkage map of eggplant developed in this work anchor the most informative previously published genetic maps of eggplant using common markers.