The DOI matches its Crossref record; 7 of the 7 references it cites were found in a registry or an index.
Methods and approaches in the topology-based analysis of biological pathways
Open accessAbstract
The goal of pathway analysis is to identify the pathways significantly impacted in a given phenotype. Many current methods are based on algorithms that consider pathways as simple gene lists, dramatically under-utilizing the knowledge that such pathways are meant to capture. During the past few years, a plethora of methods claiming to incorporate various aspects of the pathway topology have been proposed. These topology-based methods, sometimes referred to as "third generation," have the potential to better model the phenomena described by pathways. Although there is now a large variety of approaches used for this purpose, no review is currently available to offer guidance for potential users and developers. This review covers 22 such topology-based pathway analysis methods published in the last decade. We compare these methods based on: type of pathways analyzed (e.g., signaling or metabolic), input (subset of genes, all genes, fold changes, gene p-values, etc.), mathematical models, pathway scoring approaches, output (one or more pathway scores, p-values, etc.) and implementation (web-based, standalone, etc.). We identify and discuss challenges, arising both in methodology and in pathway representation, including inconsistent terminology, different data formats, lack of meaningful benchmarks, and the lack of tissue and condition specificity.
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Cites
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WikiPathways: Pathway Editing for the People
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Cited by
Wang, J., Vasaikar, S., Shi, Z., Greer, M., & Zhang, B. (2017) · Nucleic Acids Research · doi:10.1093/nar/gkx356 · Cited by 1,157
Yang, Z., & Michailidis, G. (2016) · Bioinformatics · doi:10.1093/bioinformatics/btv544 · Cited by 295
Pathway Analysis: State of the Art
García-Campos, M. A., Espinal-Enríquez, J., & Hernández-Lemus, E. (2015) · Frontiers in Physiology · doi:10.3389/fphys.2015.00383 · Cited by 265
DINGO: differential network analysis in genomics
Ha, M. J., Baladandayuthapani, V., & Do, K.-A. (2015) · Bioinformatics · doi:10.1093/bioinformatics/btv406 · Cited by 120
Rangaraju, S., Raza, S. A., Pennati, A., Deng, Q., Dammer, E. B., Duong, D., Pennington, M. W., Tansey, M. G., Lah, J. J., Betarbet, R., et al. (2017) · Journal of Neuroinflammation · doi:10.1186/s12974-017-0906-6 · Cited by 75
Metadata
- Authors
- Mitrea, C., Taghavi, Z., Bokanizad, B., Hanoudi, S., Tagett, R., Donato, M., Voichiţa, C., & Drăghici, S.
- Venue
- Frontiers in Physiology
- Publisher
- Frontiers Media SA
- Published
- 2013
- Volume
- 4
- Pages
- 278-278
- ISSN
- 1664-042X (ISSN-L)
- OpenAlex
- W2109912704
- Cited by
- 218
- References
- 7
- FWCI
- 7.93
- Type
- journal article
- Language
- en
- Open access
- gold
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- Mitrea, C., Taghavi, Z., Bokanizad, B., Hanoudi, S., Tagett, R., Donato, M., Voichiţa, C., & Drăghici, S. (2013). Methods and approaches in the topology-based analysis of biological pathways. Frontiers in Physiology. https://doi.org/10.3389/fphys.2013.00278
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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