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Cited by 265

The DOI matches its Crossref record; 85 of the 85 references it cites were found in a registry or an index.

Pathway Analysis: State of the Art

Open access
García-Campos, Miguel A., Espinal-Enríquez, Jesús, Hernández-Lemus, Enrique·2015·Frontiers in Physiology

Abstract

Pathway analysis is a set of widely used tools for research in life sciences intended to give meaning to high-throughput biological data. The methodology of these tools settles in the gathering and usage of knowledge that comprise biomolecular functioning, coupled with statistical testing and other algorithms. Despite their wide employment, pathway analysis foundations and overall background may not be fully understood, leading to misinterpretation of analysis results. This review attempts to comprise the fundamental knowledge to take into consideration when using pathway analysis as a hypothesis generation tool. We discuss the key elements that are part of these methodologies, their capabilities and current deficiencies. We also present an overview of current and all-time popular methods, highlighting different classes across them. In doing so, we show the exploding diversity of methods that pathway analysis encompasses, point out commonly overlooked caveats, and direct attention to a potential new class of methods that attempt to zoom the analysis scope to the sample scale.

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Metadata

Authors
García-Campos, M. A., Espinal-Enríquez, J., & Hernández-Lemus, E.
Venue
Frontiers in Physiology
Published
2015-12-17
Volume
6
Pages
383-383
ISSN
1664-042X (ISSN-L)
OpenAlex
W2224812643
Cited by
265
References
85
FWCI
6.30
Type
journal article
Language
en
Open access
gold

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CoChat. (2026). Citation check: Pathway Analysis: State of the Art. https://app.cochat.ai/papers/10.3389/fphys.2015.00383
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García-Campos, M. A., Espinal-Enríquez, J., & Hernández-Lemus, E. (2015). Pathway Analysis: State of the Art. Frontiers in Physiology. https://doi.org/10.3389/fphys.2015.00383

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.