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Gene prioritization through geometric-inspired kernel data fusion

机译:通过几何启发式内核数据融合确定基因优先级

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摘要

In biology there is often the need to discover the most promising genes, among a large list of candidate genes, to further investigate. While a single data source might not be effective enough, integrating several complementary genomic data sources leads to more accurate prediction.
机译:在生物学中,经常需要发现大量候选基因中最有前途的基因,以便进一步研究。虽然单个数据源可能不够有效,但整合多个互补基因组数据源会导致更准确的预测。

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