MicroPheno: predicting environments and host phenotypes from 16S rRNA gene sequencing using a k-mer based representation of shallow sub-samples
Author(s) -
Ehsaneddin Asgari,
Kiavash Garakani,
Alice C. McHardy,
Mohammad R. K. Mofrad
Publication year - 2018
Publication title -
bioinformatics
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 3.599
H-Index - 390
eISSN - 1367-4811
pISSN - 1367-4803
DOI - 10.1093/bioinformatics/bty652
Subject(s) - representation (politics) , 16s ribosomal rna , host (biology) , phenotype , gene , genetics , computational biology , biology , ribosomal rna , politics , political science , law
MicroPheno: predicting environments and host phenotypes from 16S rRNA gene sequencing using a k-mer based representation of shallow sub-samples Ehsaneddin Asgari, Kiavash Garakani, Alice C. McHardy, Mohammad R.K. Mofrad Molecular Cell Biomechanics Laboratory, Departments of Bioengineering and Mechanical Engineering, University of California, Berkeley, CA, 94720, USA, Computational Biology of Infection Research, Helmholtz Center for Infection Research, 38124 Braunschweig, Germany and Molecular Biophysics and Integrated Bioimaging, Lawrence Berkeley National Lab, Berkeley, CA, 94720, USA
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