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The lithospheric map we produced compares well with those derived from previous CHAMP and Swarm models.
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By assigning a species tag to each node in the molecular-interaction map, we produce five tissue-specific sub-maps (Blood Peripheral Blood Mononuclear Cell (Blood_PBMC), Blood Peripheral Blood Mononuclear Cell plus Polymorphonuclear leukocytes (Blood_PBMC_PMN), cartilage, Synovial Fibroblast and synovial Polymorphonuclear leukocytes (synovial_PMN)).
According to Forbes: The heat maps we produce uncannily resemble the political map of the country showing that the Government is presiding over a wholesale shift of resources predominantly from the north to the south of England.
For mapping purposes we produced an F2 mapping population from a single pair of F1 full sibling in a cross between a first-generation, lab-reared, long-beaked female and short-beaked male.
Some unassigned markers could be mapped to specific chromosomal positions in one or more of the linkage maps that we produced (results not shown).
The de novo genome maps that we produced with single-molecule data alone have assembly N50 of ≥4.6 Mb.
For the wild mapping parent, we produced transcriptome sequence data via 454 sequencing (454 Life Sciences, Branford, CT) as follows: RNA was extracted from mature leaves, bracts, florets, and developing ovules collected from a single C. palaestinus plant using a combined trizol (Invitrogen, Carlsbad, CA) and RNeasy mini column (Qiagen, Valencia, CA) method.
In principle, the use of optical maps should be straightforward: since we know the restriction enzyme used to create the optical map, we can produce an in silico digest of the contigs (a list of fragments that would theoretically result by digesting the corresponding DNA).
We produced maps for each of the mapping parents, with subsequent integration into sex-specific maps and finally a merged map.
Then, using an OWA operator (as a GIS routine), we produced maps for the three solutions, which were reclassified in five priority levels (very low, low, medium, high and very high).
So, in order to facilitate merely looking, we produced maps of the global distributional impacts with color-coded values of (Deltamathbf {X}(i,j) = sum_{t=1993}^{t=2013}Delta X_{t}^{prime}(i,j)). Figure 6 shows the total, globally mean-centered change over a period of 22 years spanning 1992-2013.
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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