Uncovering the genetics of asthma: A comparison of gene regulatory networks

Additional Metadata
Keywords	network analysis; node embedding; network comparison; genomics; asthma; machine learning; single cell data; imputation; dropouts; effective resistance distance; graph distance; radial basis function; gene affinity profiles; genetic interaction network; gene regulatory network
Thesis Advisor	Dekker, R
Persistent URL	hdl.handle.net/2105/62136
Series	Econometrie
Organisation	Erasmus School of Economics
Citation APA APA Style APA-ALL Style AAA Style Cell Style Chicago Style Harvard Style IEEE Style MLA Style Nature Style Vancouver Style American-Institute-of-Physics Style Council-of-Science-Editors Style BibTex Format Endnote Format RIS Format CSL Format DOIs only Format	Hendrickx, C.P.D. (2022). Uncovering the genetics of asthma: A comparison of gene regulatory networks. In Econometrie.http://hdl.handle.net/2105/62136

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