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Herein, we propose a novel epitope prediction method based on amino acid pairs and patch analysis.
Patch analysis showed that relationship between patch number and patch size derived previously at the national level can be applied to the Jing-Jin-Ji Urban Agglomeration despite the discrepancies in temporal scale and urban administrative hierarchy.
From this graph, patch analysis displayed a cyclic correlation between a metric based on potential dispersal flux and the population density, outlining the strong role of landscape connectivity in the population spread.
For patch analysis, watershed segmentation was applied to the complementary image of the average response image described above.
EpiSearch is based on a patch analysis that identifies spatial contiguous clusters of residues on the surface of the antigen with similar physical-chemical properties as found in the phage display sequences.
To this end we utilized our previously mentioned in silico analysis to identify potential TCF/LEF1-binding sites that could represent Wnt response elements (WRE) within the human HMGA2 loci (http://genome.ucsc.edu/: for the genomic upstream sequences and http://www.gene-regulation.com/cgi-bin/pub/programs/patch/bin/patch.cgi: PATCH analysis for transcription binding sites).
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To answer this question, we introduce a new analysis approach that combines a novel scene-patch analysis with generalized linear mixed models (GLMMs).
Specifically, we combine a scene-patch analysis with a statistical modeling approach that allows for directly describing the relationship between continuous feature values and fixation probability.
First, we present a scene-patch analysis that allows for fully describing the relationship between continuous feature values and fixation probability.
Three principal analyses were utilized: (1) patch content analysis, (2) corridor content analysis, and (3) network structure analysis.
Patch clamp analysis is according to [34], [44] and is detailed in supplementary Text S1.
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