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This constraint means that if a CNV spans multiple genes, it is impossible to determine its approximate size.
The connectivity of any node (gene), i.e. the number of other genes it is linked to, is measured as its node degree (k).
We have come to think that if something is "in our genes", it is our inevitable destiny.
With just 485 genes, it is the tiniest known free-living bacterium.
At a time when technology can probe the minutest details of organisms, down to their very genes, it is refreshing occasionally to refocus one's gaze from the perspective of human vision.
Because this is also true of AP2 genes, it is likely that OsCOL4 suppresses Ehd1 by inducing AP2 expression.
Furthermore, by mapping the output of each gene to the inputs of other genes, it is possible to reverse engineer developmental circuits and even whole networks.
However, given the disproportionately large size of the FAT genes, it is still unclear if FAT gene mutations are 'passenger' or 'driver' mutations in cancer.
Because this duplication contains 4 genes it is not immediately clear which gene is responsible for the observed behavioral differences.
With subsequent marking of any gene, or groups of genes, it is possible to zoom in to the clustering visualization.
" their surrounding genes" it is misleading.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com