KeyPathwayMiner - De-novo network enrichment by combining multiple OMICS data and biological networks

Jan Baumbach, Nicolas Alcaraz, Josch K. Pauling, Richa Batra, Eudes Guilherme Vieira Barbosa, Anne Geske Lindhard Christensen, Henrik Ditzel

Publikation: Konferencebidrag uden forlag/tidsskriftPosterForskningpeer review

Resumé

We tackle the problem of de-novo pathway extraction. Given a biological network and a set of case-control studies, KeyPathwayMiner efficiently extracts and visualizes all maximal connected sub-networks that contain mainly
genes that are dysregulated, e.g., differentially expressed, in most cases studied. The exact quantities for ``mainly'' and ``most'' are modeled with two
easy-to-interpret parameters that allow the user to control the number of outliers (not dysregulated genes/cases) in the solutions. We developed two slightly varying models that fall into the class of NP-Hard optimization problems and designed a set of algorithms to tackle the combinatorial explosion of the search space. During the presentation we will demonstrate how to: Import and process the data, set the parameters for the two models, compute and visualize the key pathways, judge and statistically evaluate the results, explain the different algorithms. Finally, we will discuss on-going work, future extensions, and present yet unpublished results.
OriginalsprogEngelsk
Publikationsdato10. jul. 2015
StatusUdgivet - 10. jul. 2015
Begivenhed23rd Annual International Conference on Intelligent Systems for Molecular Biology - Dublin, Irland
Varighed: 10. jul. 201514. jul. 2015

Konference

Konference23rd Annual International Conference on Intelligent Systems for Molecular Biology
LandIrland
ByDublin
Periode10/07/201514/07/2015

Fingeraftryk

Explosions
Genes

Citer dette

Baumbach, J., Alcaraz, N., Pauling, J. K., Batra, R., Vieira Barbosa, E. G., Christensen, A. G. L., & Ditzel, H. (2015). KeyPathwayMiner - De-novo network enrichment by combining multiple OMICS data and biological networks. Poster session præsenteret på 23rd Annual International Conference on Intelligent Systems for Molecular Biology, Dublin, Irland.
Baumbach, Jan ; Alcaraz, Nicolas ; Pauling, Josch K. ; Batra, Richa ; Vieira Barbosa, Eudes Guilherme ; Christensen, Anne Geske Lindhard ; Ditzel, Henrik. / KeyPathwayMiner - De-novo network enrichment by combining multiple OMICS data and biological networks. Poster session præsenteret på 23rd Annual International Conference on Intelligent Systems for Molecular Biology, Dublin, Irland.
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Baumbach, J, Alcaraz, N, Pauling, JK, Batra, R, Vieira Barbosa, EG, Christensen, AGL & Ditzel, H 2015, 'KeyPathwayMiner - De-novo network enrichment by combining multiple OMICS data and biological networks' 23rd Annual International Conference on Intelligent Systems for Molecular Biology, Dublin, Irland, 10/07/2015 - 14/07/2015, .

KeyPathwayMiner - De-novo network enrichment by combining multiple OMICS data and biological networks. / Baumbach, Jan; Alcaraz, Nicolas; Pauling, Josch K.; Batra, Richa; Vieira Barbosa, Eudes Guilherme; Christensen, Anne Geske Lindhard; Ditzel, Henrik.

2015. Poster session præsenteret på 23rd Annual International Conference on Intelligent Systems for Molecular Biology, Dublin, Irland.

Publikation: Konferencebidrag uden forlag/tidsskriftPosterForskningpeer review

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AU - Batra, Richa

AU - Vieira Barbosa, Eudes Guilherme

AU - Christensen, Anne Geske Lindhard

AU - Ditzel, Henrik

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N2 - We tackle the problem of de-novo pathway extraction. Given a biological network and a set of case-control studies, KeyPathwayMiner efficiently extracts and visualizes all maximal connected sub-networks that contain mainlygenes that are dysregulated, e.g., differentially expressed, in most cases studied. The exact quantities for ``mainly'' and ``most'' are modeled with twoeasy-to-interpret parameters that allow the user to control the number of outliers (not dysregulated genes/cases) in the solutions. We developed two slightly varying models that fall into the class of NP-Hard optimization problems and designed a set of algorithms to tackle the combinatorial explosion of the search space. During the presentation we will demonstrate how to: Import and process the data, set the parameters for the two models, compute and visualize the key pathways, judge and statistically evaluate the results, explain the different algorithms. Finally, we will discuss on-going work, future extensions, and present yet unpublished results.

AB - We tackle the problem of de-novo pathway extraction. Given a biological network and a set of case-control studies, KeyPathwayMiner efficiently extracts and visualizes all maximal connected sub-networks that contain mainlygenes that are dysregulated, e.g., differentially expressed, in most cases studied. The exact quantities for ``mainly'' and ``most'' are modeled with twoeasy-to-interpret parameters that allow the user to control the number of outliers (not dysregulated genes/cases) in the solutions. We developed two slightly varying models that fall into the class of NP-Hard optimization problems and designed a set of algorithms to tackle the combinatorial explosion of the search space. During the presentation we will demonstrate how to: Import and process the data, set the parameters for the two models, compute and visualize the key pathways, judge and statistically evaluate the results, explain the different algorithms. Finally, we will discuss on-going work, future extensions, and present yet unpublished results.

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Baumbach J, Alcaraz N, Pauling JK, Batra R, Vieira Barbosa EG, Christensen AGL et al. KeyPathwayMiner - De-novo network enrichment by combining multiple OMICS data and biological networks. 2015. Poster session præsenteret på 23rd Annual International Conference on Intelligent Systems for Molecular Biology, Dublin, Irland.