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

Baum, Katharina; Rajapakse, Jagath C.; Azuaje, Francisco


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  "description": "<p><strong>Baum_et_al_2019_Supplementary_Figures.pdf:&nbsp;</strong>Supplementary Figures S1-S4. Legends are included under each figure.</p>\n\n<p><strong>sbm-for-correlation-based-networks-master.zip:&nbsp;</strong>Archived source code of R and Python functions for the&nbsp;analyses&nbsp;and example workflow description&nbsp;at time of publication. Files are maintained at https://gitlab.com/biomodlih/sbm-for-correlation-based-networks and&nbsp;https://gitlab.com/kabaum/sbm-for-correlation-based-networks.</p>", 
  "license": "http://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Bioinformatics and Modelling, Luxembourg Institute of Health, and Mathematical Modelling of Cellular Processes, Max Delbr\u00fcck Center for Molecular Medicine in the Helmholtz Association", 
      "@id": "https://orcid.org/0000-0001-7256-0566", 
      "@type": "Person", 
      "name": "Baum, Katharina"
    }, 
    {
      "affiliation": "School of Computer Science and Engineering, Nanyang Technological University", 
      "@id": "https://orcid.org/0000-0001-7944-1658", 
      "@type": "Person", 
      "name": "Rajapakse, Jagath C."
    }, 
    {
      "affiliation": "Bioinformatics and Modelling, Luxembourg Institute of Health", 
      "@id": "https://orcid.org/0000-0002-9207-9072", 
      "@type": "Person", 
      "name": "Azuaje, Francisco"
    }
  ], 
  "url": "https://zenodo.org/record/3363060", 
  "datePublished": "2019-08-08", 
  "version": "v3", 
  "keywords": [
    "biomolecular networks", 
    "edge relevance", 
    "missing and spurious edges", 
    "network-based omics analysis", 
    "weighted stochastic block model"
  ], 
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  "identifier": "https://doi.org/10.5281/zenodo.3363060", 
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  "@type": "Dataset", 
  "name": "Analysis of correlation-based biomolecular networks from different omics data by fitting stochastic block models"
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