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By virtue of in silico experiments, factors such as scaffold stiffness, porosity, resorption kinetics, pore size and pre-seeding are analyzed in a specific bone tissue application found in the literature.
These results suggest that when reads with a hit are analyzed in a specific species, we most likely find homologous gene sequences with coding capacity.
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It is noteworthy, however, that when PCSK pairs were analyzed in a tissue specific setting other strong correlations can be observed.
The main conclusion of this paper is that interesting inferences can be gleaned from genome-wide microarray data (with or without mathematical models) if gene-gene correlations are analyzed in a pathway specific manner.
For both allele-specific gene expression and chromatin interactions, the new data can be analyzed in a locus-specific manner without the need for high-throughput genomic technologies, but equally it can be cost- and time-effective to screen many different loci simultaneously.
Each tSNP was analyzed in a gender-specific population under each model.
Parental SNPs across genes were identified as previously described for ChIP-seq datasets, except that reads were analyzed in a strand-specific manner.
At the first level, data were analyzed in a participant-specific fashion, with each word type, baseline, and pseudowords modeled separately and convolved with a canonical hemodynamic response function (HRF).
Hit lists from screens targeting the same virus were combined and analyzed in a virus-specific way, as well as all data pooled for pan-viral analysis of host restriction and host dependency factors.
In order to analyze if a specific sequence motif is preferred as a spacer between multiple ACGT elements across all promoters, we developed consensus sequences from all spacers observed.
Gp130-dependent gene expression was analyzed in a previously established hepatocyte-specific gp130 knockout mouse model.
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