PathWalks: identifying pathway communities using a disease-related map of integrated information Article Swipe
Evangelos Karatzas
,
Margarita Zachariou
,
Marilena M. Bourdakou
,
George Minadakis
,
Anastasis Oulas
,
George Kolios
,
Alex Delis
,
George M. Spyrou
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1093/bioinformatics/btaa291
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.1093/bioinformatics/btaa291
Motivation Understanding the underlying biological mechanisms and respective interactions of a disease remains an elusive, time consuming and costly task. Computational methodologies that propose pathway/mechanism communities and reveal respective relationships can be of great value as they can help expedite the process of identifying how perturbations in a single pathway can affect other pathways. Results We present a random-walks-based methodology called PathWalks, where a walker crosses a pathway-to-pathway network under the guidance of a disease-related map. The latter is a gene network that we construct by integrating multi-source information regarding a specific disease. The most frequent trajectories highlight communities of pathways that are expected to be strongly related to the disease under study. We apply the PathWalks methodology on Alzheimer's disease and idiopathic pulmonary fibrosis and establish that it can highlight pathways that are also identified by other pathway analysis tools as well as are backed through bibliographic references. More importantly, PathWalks produces additional new pathways that are functionally connected with those already established, giving insight for further experimentation. Availability and implementation https://github.com/vagkaratzas/PathWalks. Supplementary information Supplementary data are available at Bioinformatics online.
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- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.1093/bioinformatics/btaa291
- https://academic.oup.com/bioinformatics/article-pdf/36/13/4070/33459024/btaa291.pdf
- OA Status
- hybrid
- Cited By
- 9
- References
- 87
- Related Works
- 10
- OpenAlex ID
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All OpenAlex metadata
Raw OpenAlex JSON
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- DOI
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https://doi.org/10.1093/bioinformatics/btaa291Digital Object Identifier
- Title
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PathWalks: identifying pathway communities using a disease-related map of integrated informationWork title
- Type
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articleOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
- Publication date
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2020-04-27Full publication date if available
- Authors
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Evangelos Karatzas, Margarita Zachariou, Marilena M. Bourdakou, George Minadakis, Anastasis Oulas, George Kolios, Alex Delis, George M. SpyrouList of authors in order
- Landing page
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https://doi.org/10.1093/bioinformatics/btaa291Publisher landing page
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https://academic.oup.com/bioinformatics/article-pdf/36/13/4070/33459024/btaa291.pdfDirect link to full text PDF
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YesWhether a free full text is available
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hybridOpen access status per OpenAlex
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https://academic.oup.com/bioinformatics/article-pdf/36/13/4070/33459024/btaa291.pdfDirect OA link when available
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10Other works algorithmically related by OpenAlex
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