Tracking Human Gut Microbiome Changes Resulting from a Colonoscopy
L. Smarr, E. R. Hyde, D. McDonald, W. J. Sandborn, R. Knight. Methods of Information in Medicine. 56(6):442-447 (2017).
Bringing the Dynamic Microbiome to Life with Animations
Y. Vazquez-Baeza, A. Gonzalez, L. Smarr, D. McDonald, J. T. Morton, J. A. Navas-Molina, and R. Knight. Cell Host and Microbe, vol. 21, pp 7-10. (2017).
Using Machine Learning to Identify Major Shifts in Human Gut Microbiome Protein Family Abundance in Disease
Proceedings Of The 2016 IEEE International Conference On Big Data. M. Yazdani, B. C. Taylor, J. W Debelius, W. Li, R. Knight, and L. Smarr. (2016).
Using Topological Data Analysis to find discrimination between microbial states in human microbiome data
Mehrdad Yazdani, Larry Smarr and Rob Knight. (2016).
Using Pairwise Difference Features to Measure Temporal Changes in the Microbial Ecology
The exponential affordability of DNA sequencing technologies has enabled not only the accessible and rapid sequencing of the human genome, but the opportunity to sequence vast numbers of multi-cellular organism and the tiniest microbes.