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Using data from ∼1400 nests of 23 species, we generated nest survival curves for groups of altricial species defined by nest substrate (ground, shrub, tree, or culvert).
For each species, we generated predictions of current and future distribution based on the vegetation and climate datasets described above, as well as stream proximity as a proxy for riparian vegetation.
To explore the effect of sampling differences between the two species, we generated 10,000 pseudo-random samples of two individuals from each of our six A. lyrata populations, thereby mimicking the A. thaliana sampling strategy of Nordborg et al. [79].
Since the number of presence localities varied for each species, we generated null data sets with the number of random points per distribution equal to 50, 205, 405, or 695 data points, which represent the range of presence points available to model each species.
For seven species, we generated the sequence by targeted mapping and sequencing.
If multiple sequences were available for a species, we generated a consensus sequence.
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QTL data are available for various plant species and we generated sets of high-quality biological process predictions for different plant species, including major crops [ 34].
Based on the conserved and functional domains of VHL seen in different species [13], we generated a series of VHL truncated mutants fused with an HA tag (Figure 4D).
To examine if this phenotype is cell type or species dependent, we generated shRNA-mediated OLA1 knockdown cells derived from human breast cancer cell line MDA-MB-231.
With evidence suggesting that PrPC in our BHS brain tissues was intact and present at detectable levels, and that the CER assay can reproduce mouse TSE species barriers, we generated CER assay substrates from BHS brain to assess the conversion of BHS PrPC by TSE agents.
We randomly generated 200 π vectors with IC evenly distributed between 0 and 2. For each π and a given number of species, we first generated a 200-column alignment by sampling sequences in the leaf nodes using the CTMP model with the rate matrix Q parameterized by π [as in Equation (10)].
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com