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This operation accumulates "piles" of independently aligned single molecule maps that are then isolated from their seed map scaffolds and separately assembled into contigs using the map assembler.
In Seed Map, we aimed to improve the choice of reference groups by attempting to identify natural clusters within the dataset prior to embedding.
The construction procedure used the following pseudo-code algorithm: (i) initialised consensus map with the seed map; and (ii) for each chromosome, we found a subset of linkage groups for this chromosome and repeated until subset was empty for each group.
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In this work, we describe how a sorted search index and the use of a composite seeding strategy can help to efficiently and sensitively detect seed map-to-sequence alignments [ 20].
We call the resulting consensus maps seed maps.
The previous step generates a set of seed maps.
Analyzing only the differential expression and miRNA-mRNA seed mapping led to noisy results.
The sequential trimming approach discussed here, or seed mapping and extension, are likely to result in significantly higher mapping rates.
We accomplish this through pairwise alignment of the complete map data set against the entire collection of seed maps.
The 17 downregulated genes and 5 upregulated genes (P value ≤ 0.1) did not have any miR-142 seed mapping.
The seed maps typically cover most of the genome and they reliably approximate highly confident paths in the graph.
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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