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Both read depth and read density are presented in units of read depth per million bases acquired to obtain higher scale values.
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Mean read density values for exons, introns, and intergenic regions were computed in units of reads per kilobase of exon/intron/intergenic per million mapped reads [ 23].
mRNA and footprint read density were calculated in units of reads per kilobase million (RPKM) to normalize for gene length and total reads per sequencing run.
Once all reads were mapped, ERANGE reported gene expression in units of reads per kilobase of exon and per million tags sequenced (RPKM).
The following metrics are based on coverage: the number of reads that cover a given genomic position (in units of reads per base).
FP and mRNA densities were calculated in units of reads per kilobase per million (RPKM) in order to normalize for gene length and total number of reads per sequencing run.
For each transcript, by tabulating the number of reads mapped and by normalizing with sample size and transcript length, we can calculate the expression level of transcripts and genes in the unit of reads per kilo base per million mapped reads (RPKM).
Using these reliable reads, we compute pseudogene expression levels in units of Reads per Kilobase of Uniquely mappable transcript per Million reads (RPKUM).
Total weighted reads and AGAP transcript lengths were used to calculate a normalized transcript abundance level in units of Reads Per Kilobase per Million reads mapped (RPKMs), for every AGAP in every tissue type [ 32].
Dynamical reservoirs are generally formed by a fully recurrent neural network with fixed, typically sparse, random weights, and one further layer of external units connected to the internal units to read out the dynamics of the network.
To provide a solution to this need, a wireless multichannel telemetry unit capable of reading strain is required.
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