Sentence examples for mapping we chose from inspiring English sources

Since pbrt to our knowledge doesn't facilitate a UV-to-triangle mapping, we chose to assume equally sized triangles and uniformly sample among these.

To evaluate the usability of the above developed markers for genetic mapping, we chose a crinkly leaf mutant from the Hedou12 mutagenesis population.

To clarify the correspondence between the previous linkage map [ 16] and the present map, we chose 106 SSR markers that were distributed genome-wide in the previous map.

For genetic diversity assessment, linkage analysis and construction of the condor genetic map, we chose 121 related individuals that formed a condor resource population.

In order to better evaluate the effect of combing segregation data form both parents in a single map, we chose to present the separate parental species maps built using a widely used approach and software (pseudo-testcross and Mapmaker [ 4]) and compare them with the consensus map resulting form the integrated segregation data analyzed with Outmap.

Given the paucity of available common bean sequences and our interest in generating sequence reads long enough to be useful for the design of primers for mapping onto the common bean map, we chose the Roche 454 sequencing method (see materials and methods).

To investigate the potential limitations in the between-approach agreement and relative benefits gained by an integrative analysis among the currently available high-throughput quantitative genetic interaction maps, we chose representative example datasets across the spectrum of high-throughput interaction screening approaches currently used for Saccharomyces cerevisiae.

To minimize the mismatch between texture maps, we choose to use multi-channel Mutual Information criteria, often used to match 2D and 3D medical images from different modalities [16].

Because there were only 45 common SNP markers among the four mapping populations, we chose individual SNP maps to do colinearity comparison with the integrated map.

Evidently, the higher sequencing coverage permits the use of larger windows covering the same physical and genetic intervals and consequently more accurate mapping, so we chose 15 SNPs as our analysis parameters.

For the transcriptional and sRNA mapping analyses we chose to analyze at the family level.