Sentence examples for mapping we used from inspiring English sources

After mapping, we used samtools sort and mpileup commands (Li and Durbin 2009) to parse the mapping results.

For LEO ROTI mapping, we used the same grid as for the ground-based GPS data: corrected geomagnetic coordinates, grid cells 8 min MLT by 2° MLAT and 00 24 h daily data accumulation.

To construct the mapping, we used a feedforward neural network with variable structure, which is a network in which the structure is determined by minimizing the error on the training set.

In individual family mapping, we used the family in which a rare QTL was segregating.

For retinotopic mapping we used 25 horizontal slices (TR = 3000 ms, TE = 30; 64×64 matrix, voxel size 3×3×3 mm).

For a straightforward validation of subclass mapping, we used two data sets of multiple normal tissue types acquired on two different generations of the Affymetrix GeneChip oligonucleotide microarray platform, Multi-A [5] and Multi-B [6].

For feature mapping, we use the same method as we do with ImageNet 10.

After feature mapping, we use the dereverberated features for acoustic modeling.

In the audio visual mapping, we use Fused HMMs of the first layer to select the best cluster.

In QTL mapping, we use known (observable) marker information to infer unknown (unobservable) QTL genotypes based on their co-segregation in a population.

For read mapping, we use mrsFAST (F.Hach et al., unpublished data), a cache-oblivious short read mapper recently developed as an extension of mrFAST (Alkan et al., 2009).