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We applied a number of stringent quality checks to all genotype calls derived from these arrays to define a subset of high quality SNPs (see Methods).
Towards this goal, we have used haploid cell lines to experimentally validate the use of high-density SNP arrays to define genome wide haplotypes and candidate regions, using a small ALS family.
To avoid threshold effects caused when modestly induced genes wobble across the two-fold threshold, we applied a more stringent criterion (>2 fold in all three arrays) to define the set of genes induced at each time-point.
In our present study we used the same highly standardised setting of primary human monocyte derived macrophages activated with LPS and IFNγ and whole genome oligonucleotide arrays to define the complete transcriptome of macrophages in response to inflammatory activation.
Towards this goal, we have used haploid cell lines to experimentally validate the use of high-density single nucleotide polymorphism (SNP) arrays to define genome-wide haplotypes and candidate regions, using a small amyotrophic lateral sclerosis (ALS) family as a prototype.
Here we report the use of these arrays to define the genomic profile of 47 primary breast tumors and 18 breast cancer cell lines.
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To our knowledge this is the most extensive study using high-resolution SNP-arrays to define the genetic alterations in this subgroup of CRC patients.
The purpose of conducting these arrays is to define the optimum level for each controllable parameter which cooperates to get the better fitness function value.
We used patch-clamp electrophysiology coupled to electron microscopy and multi-electrode arrays (MEA) to define the physiological impact of the Q555X mutation at excitatory and inhibitory terminals of primary SynI KO hippocampal neurons in which either wild-type (WT) or mutant human SynI (hSynI) was expressed by lentiviral transduction.
However, it must be pointed out that the actual sizes of these regions of overlap may change according to the resolution of the array used to define them.
Globally, these findings underscore the efficiency and accuracy of ChIP-Seq and expression array technologies to define a Pax8-dependent gene network, which allowed us to identify biological functions of Pax8 in thyroid cells.
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