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The MCS measures 2D coordinates of a number of markers with multiple cameras; these measurements are then used to calculate the 3D coordinates of markers.
In order to decrease the information loss caused by single cutoff value and improve diagnosis efficiency (DE), we explore the integrative application of multiple tumor markers with multiple cutoff values systematically by developing an optimization algorithm named MVMTM.
Markers with multiple matches to multiple chromosomes (or no chromosome matches) were not assigned to a chromosome.
For those markers with multiple bands, the amplicon sizes in Additional file 1 could help to distinguish those amplicons.
The challenge is to integrate approaches using single markers with multiple gene signatures to find optimal predictive and prognostic tools.
A few markers with multiple entries in a single dataset were removed because the segregation signatures of the multiple entries did not resemble each other.
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Removal of the marker with multiple singletons and rescoring the data for the other singletons as missing resulted in a map of 97 cM.
For example, the genera Ahnfeltiopsis (Gigartinales), Peyssonnelia (Peyssonneliales) and Gelidium (Gelidiales) all have clusters of sequences for at least one marker with multiple species names applied.
Each recombination bin or skeletal marker segregated with multiple add-on markers, for a high-density genetic map.
The aim of our study was to measure a panel of systemic biochemical markers associated with multiple biological processes involved in the formation of bone metastases.
Also, if there are no additional ways to infer relationships (e.g. in the absence of comparable markers, as with multiple chromosomes in metagenomic analyses) the genome signature may help to cluster chromosomes, although the intragenomic δ* scores can be relatively high in multichromosomal genomes from prokaryotes.
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