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Titlebook: Computational Intelligence Methods for Bioinformatics and Biostatistics; 13th International M Andrea Bracciali,Giulio Caravagna,Roberto Tag

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樓主: 反抗日本
51#
發(fā)表于 2025-3-30 11:21:45 | 只看該作者
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發(fā)表于 2025-3-30 13:02:22 | 只看該作者
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發(fā)表于 2025-3-30 20:36:29 | 只看該作者
https://doi.org/10.1007/978-3-322-91134-6g the literature search space to discover recently introduced disease correlations. Results show that our system can produce reasonable hypotheses for disease correlations, and that document stratification is an important aspect to take into account when using scientific literature.
54#
發(fā)表于 2025-3-30 22:12:26 | 只看該作者
Computational Intelligence Methods for Bioinformatics and Biostatistics13th International M
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發(fā)表于 2025-3-31 01:13:59 | 只看該作者
Module Detection Based on Significant Shortest Paths for the Characterization of Gene Expression Da centrality measures and the identification of the cut vertices allowed to unveil important nodes in the disease module network. The results obtained were promising, as shown by the detection of key genes for the characterization of the studied disease.
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發(fā)表于 2025-3-31 06:55:48 | 只看該作者
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發(fā)表于 2025-3-31 11:10:39 | 只看該作者
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發(fā)表于 2025-3-31 15:53:32 | 只看該作者
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發(fā)表于 2025-3-31 17:39:34 | 只看該作者
A Novel Algorithm for CpG Island Detection in Human Genome Based on Clustering and Chaotic Particleuate its performance, we used six sequences from NCBI, and five measures of performance: sensitivity (SN), specificity (SP), accuracy (ACC), performance coefficient (PC), and correlation coefficient (CC). We compared our approach to the existing methods of CpG islands detection in the human genome.
60#
發(fā)表于 2025-3-31 23:38:34 | 只看該作者
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