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For deletion data, we learned a noise model to distinguish real signals from random fluctuations using an iterative method.
We consider a simple noise model for deletion data, that each data point is the superposition of the real signal and a reasonably small Gaussian noise independent of the gene and the time point.
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In order to determine the GECN in the present study, 35 SSR marker (5 from each D-genome chromosome) based deletion data for 339 DGRH1 plants belonging to 29RH11 families was used to calculate the segregation ratio for each unique deletion mutation.
In particular, deletion data allow for the detection of direct regulatory activities with strong responses upon the deletion of the regulator while perturbation data provide richer information for the identification of weaker and more complex types of regulation.
Whole genome analyses are not available for these organisms, but genomic deletion data have been reported (34 ).
Deletion data were available for 105 samples from 65 patients for analysis of copy neutral and copy loss LOH.
At the same time, gene deletion data are essential for understanding pathogenesis and, more importantly, for identifying potential targets for antibacterial intervention.
While deletion data is good for detecting simple, direct regulatory events, they may not be sufficient for decoding those that are more complicated.
Furthermore, for all genes with nonstandard arm locations for which corresponding ESTs and deletion bin data were available, the 3B arm locations obtained from the sequence data and the deletion data disagreed.
A similar analysis of ChIP-chip data for 70 chromatin proteins (Venters et al. 2011) and expression data for deletion mutants in the same chromatin proteins (Lenstra et al. 2011) reached a similar conclusion (Lenstra and Holstege 2012).
Realigning this balance is a more complex business than just earmarking certain types of data for deletion.
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