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Dataset . 2019
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Dataset . 2019
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Dataset . 2019
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Dataset . 2019
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ZENODO
Dataset . 2019
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ZENODO
Dataset . 2019
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Claim

Analysis of correlation-based biomolecular networks from different omics data by fitting stochastic block models

Research datakeyboard_double_arrow_right Dataset 21 Mar 2019 English Publisher:Zenodo
Authors: Baum, Katharina; Rajapakse, Jagath C.; Azuaje, Francisco;

doi: 10.5281/zenodo.3363060 , 10.5281/zenodo.2586675 , 10.5281/zenodo.2620419 , 10.5281/zenodo.2586674

Analysis of correlation-based biomolecular networks from different omics data by fitting stochastic block models

Abstract

{"references": ["Budczies J, Brockmoller SF, et al. (2013). Comparative metabolomics of estrogen receptor positive and estrogen receptor negative breast cancer: alterations in glutamine and beta-alanine metabolism. J Proteomics. 2013;94:279-88.", "Peixoto TP (2014). The graph-tool python library. 10.6084/m9.figshare.1164194", "Langfelder P, Horvath S. WGCNA (2008): an R package for weighted correlation network analysis. BMC Bioinformatics, 9:559."]}

Baum_et_al_2019_Supplementary_Figures.pdf: Supplementary Figures S1-S4. Legends are included under each figure. sbm-for-correlation-based-networks-master.zip: Archived source code of R and Python functions for the analyses and example workflow description at time of publication. Files are maintained at https://gitlab.com/biomodlih/sbm-for-correlation-based-networks and https://gitlab.com/kabaum/sbm-for-correlation-based-networks.

Related Organizations
Keywords

biomolecular networks, edge relevance, weighted stochastic block model, missing and spurious edges, network-based omics analysis

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
views
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