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Titlebook: Evolutionary Computation, Machine Learning and Data Mining in Bioinformatics; 11th European Confer Leonardo Vanneschi,William S. Bush,Mario

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樓主: 小客車
41#
發(fā)表于 2025-3-28 17:11:54 | 只看該作者
Palgrave Studies in European Union Politicsgnificant main effects. MDR produces a reduced-dimensionality representation of a dataset which classifies multi-locus genotypes into either high- or low-risk groups. The weighted fraction of cases and controls correctly labelled by this classification, the balanced accuracy, is typically used as a
42#
發(fā)表于 2025-3-28 19:52:00 | 只看該作者
Pauline Pirlot,Tom Delreux,Christine Farcyertain subgraphs of interactions or motifs appear at anomalously high frequencies. We investigate here whether the overrepresentation of these motifs can be explained by the functional capabilities of these networks. Given a framework for describing regulatory interactions and dynamics, we consider
43#
發(fā)表于 2025-3-29 01:55:13 | 只看該作者
44#
發(fā)表于 2025-3-29 04:12:47 | 只看該作者
45#
發(fā)表于 2025-3-29 08:27:20 | 只看該作者
46#
發(fā)表于 2025-3-29 12:55:06 | 只看該作者
Multiple Threshold Spatially Uniform ReliefF for the Genetic Analysis of Complex Human Diseaseshese interactions with high accuracy and in time linear in the number of genes. Our algorithm is an improvement over the SURF* algorithm, which detects genetic signals by comparing individuals close to, and far from, one another and noticing whether differences correlate with different disease statu
47#
發(fā)表于 2025-3-29 18:58:59 | 只看該作者
Time-Point Specific Weighting Improves Coexpression Networks from Time-Course Experimentseffectively identify and summarize gene-gene relationships within individual experiments. For gene-expression datasets, the Pearson correlation is often applied to build coexpression networks because it is both easily interpretable and quick to calculate. Here we develop and evaluate weighted Pearso
48#
發(fā)表于 2025-3-29 21:23:30 | 只看該作者
Inferring Human Phenotype Networks from Genome-Wide Genetic Associationsr 600 physical attributes, diseases, and behavioral traits; based on more than 6,000 genetic variants (SNPs) from Genome-Wide Association Studies data. Using phenotype-to-SNP associations, and HapMap project data, we link traits based on the common patterns of human genetic variations, expanding pre
49#
發(fā)表于 2025-3-30 00:02:09 | 只看該作者
Knowledge-Constrained K-Medoids Clustering of Regulatory Rare Alleles for Burden Testsnging due to a lack of statistical power in most feasibly sized datasets. Several statistical tests have been developed to either collapse multiple rare variants from a genomic region into a single variable (presence/absence) or to tally the number of rare alleles within a region, relating the burde
50#
發(fā)表于 2025-3-30 06:14:23 | 只看該作者
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