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In the Fugu example, Figure 2 and 3, the numerical alignment score of the (anchored) correct alignment was 13% below the score of the non-anchored alignment.
The numerical alignment scores of the (biologically correct) anchored alignments turned out to be slightly below the scores of the non-anchored default alignments.
Using MACS peak calling, FUS ChIP-seq peaks corresponding to promoter regions were identified in our data, but not in numerical alignment with Schwarts et al., which described preferential promoter association to thousands of genes (Additional file 16).
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Upon motivating principles of symbolic analysis, our analysis illustrates how the optimized numerical scoring for alignment schemes may reveal functional and causal relations among the indicator data.
It has been shown, that the numerical score of alignments produced by this heuristic can be far below the optimum [ 5, 13].
We present a new numerical algorithm that aligns a quadrilateral grid with internal alignment curves (IACs).
Table 1 should be used to compute the numerical value for the alignment.
In order to analyze and score the degree of similarity between the P. falciparum and E. coli neighborhood subnetworks a shortest-path graph kernel was used to measure the similarity between two labeled networks, and a numerical score for each alignment was assigned [ 78].
This may improve numerical stability for huge alignments.
We converted the 6-, 15- and 57-position sequence alignments to numerical encodings representing amino acid sequences of length l as binary vectors of length l×20 digits, i.e. the 20 different amino acids were encoded as orthogonal 20 digit vectors and an amino acid sequence was represented by concatenating the binary vectors corresponding to residues at each position.
In contrast, in the teleost HoxA cluster example the numerical score of the anchored alignment was around 15% above the score of the non-anchored alignment.
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