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 Style AAA Style APA 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, March 17). Uncovering the genetics of asthma: A comparison of gene regulatory networks. Econometrie. Retrieved from http://hdl.handle.net/2105/62136

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