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Include a table on the map that associates different morphological adaptations and ecological conditions.
Then a left-module isomorphism R R → R R 2 is easy to establish, by considering the map that associates with any row-finite matrix M the pair of row-finite matrices ( M 1, M 2 ), where M 1 is built from the odd-indexed columns of M, and M 2 from the even-indexed columns.
Proof The continuity of P follows immediately from the continuous dependence on data stated in Corollary 2.2 and by the continuity of the map ψ ↦ ψ ˜ of Lemma 3.5 and of the map that associates to any φ ∈ M ˜ its restriction to the interval [ − T, 0 ].
The produced intraspecific genetic map is the first saturated map that associates into 26 linkage groups corresponding to the number of cotton chromosomes for a cross between two G. hirsutum lines.
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The solution includes the equivalent parameter domain for each model and parameter mapping that associates these two models on their equivalent parameter domains.
If we denote by Φ:[1, n]→[1, m] the mapping that associates a bead i to a locus Φ(i) of the contact count matrix, this means that the contact count c kl between loci k and l is the sum of counts due to interactions between beads in Φ−1(k) and Φ−1(l).
In the sixties, inspired by the mapping that associated the area of a triangle to its three vertices, Gähler [1, 2] introduced the concept of 2-metric spaces.
These amount to diffeomorphisms on the manifold M and the transformations of the fields correspond to maps that associate an object field O with its carry along h*O under diffeomorphism h.
In the 1960s, Gähler [1, 2] tried to generalize the notion of metric and introduced the concept of 2-metric spaces inspired by the mapping that associated the area of a triangle to its three vertices.
Here we use detailed cross-species expression data to create maps that associate uncharacterized genes with different cellular processes with an emphasis on those that are not represented in model systems.
Unlike the method by Yeang and Jaakkola [ 3], DREM's ability to derive dynamic maps that associate TFs with the genes they regulate and their activation time-points has indeed led to better insights for the regulatory module being studied.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com