KNGP: A network-based gene prioritization algorithm that incorporates multiple sources of knowledge.

Chad Kimmel, Shyam Visweswaran
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Abstract

Background: Candidate gene prioritization is the process of identifying and ranking new genes as potential candidates of being associated with a disease or phenotype. Integrating multiple sources of biological knowledge for gene prioritization can improve performance.

Results: We developed a novel network-based gene prioritization algorithm called Knowledge Network Gene Prioritization (KNGP) that can incorporate node weights in addition to the usually used link weights. The online Web implementation of KNGP can handle small input files while the downloadable R software package can handle larger input files. We also provide several files of coded biological knowledge that can be used by KNGP.

Abstract Image

KNGP:一个基于网络的基因优先排序算法,包含多个知识来源。
背景:候选基因优先排序是识别和排序与疾病或表型相关的潜在候选新基因的过程。整合多种来源的生物学知识进行基因排序可以提高性能。结果:我们开发了一种新的基于网络的基因优先排序算法,称为知识网络基因优先排序(KNGP),该算法除了通常使用的链路权重外,还可以合并节点权重。KNGP的在线Web实现可以处理小的输入文件,而可下载的R软件包可以处理较大的输入文件。我们还提供了KNGP可以使用的几个编码生物学知识文件。
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