ArticleFrontiers in bioinformatics2026
A practical guide to functional enrichment analysis.
Article in Frontiers in bioinformatics, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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3 authors.
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Abstract
Functional Enrichment Analysis (FEA) has become a critical step in the analysis of omics data in recent years. As a result, numerous approaches have been rapidly developed, leading to an overflow of information that can be difficult for beginners to navigate. Most usage information on FEA methods is scattered across countless articles that often address specific problems, making it difficult to find practical recommendations and good practices. In these guidelines, we discuss the current landscape of FEA and FEA-related approaches and organize actionable knowledge to support first-timers and update veterans on advancements in the field. We aim to aid non-bioinformaticians who use FEA through the general decision-making process necessary to ensure the quality of the analysis. We also provide a practical guide that assists FEA users through the decision-making process underlying FEA and directs readers to more advanced resources for specific FEA contexts. As a basic step in any omics analysis, our practical guide may aid in rapid decision-making for FEA.
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