SEMgsa: topology-based pathway enrichment analysis with structural equation models

被引：0
作者：
Mario Grassi
Barbara Tarantino
机构：
[1] University of Pavia,Department of Brain and Behavioral Sciences
来源：
BMC Bioinformatics | / 23卷
关键词：
Pathway enrichment analysis; Pathway topology; SEM; SEMgsa; Sensitivity; Prioritization; Type I error; Power;
D O I：
暂无
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学科分类号：
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