Microbial Communities
Community Cyberinfrastructure for Advanced Microbial Ecology Research and Analysis
The CAMERA (Cyberinfrastructure for Advanced Marine Microbial Ecology Research and Analysis) community database for metagenomic data deposition is an important first step in developing methods for monitoring microbial communities.
Longitudinal flux balance analyses of a patient with episodic colonic inflammation reveals microbiome metabolic dynamics
We report the first use of constraint-based microbial community modeling on a single individual with episodic inflammation of the gastrointestinal tract.
Gastrointestinal Surgery for Inflammatory Bowel Disease Persistently Lowers Microbiome and Metabolome Diversity
Many studies have investigated the role of the microbiome in inflammatory bowel disease (IBD), but few have focused on surgery specifically or its consequences on the metabolome.
De Novo Peptide Sequencing Reveals Many Cyclopeptides in the Human Gut and Other Environments
We present a computational pipeline for automated analysis and discovery of cyclic and branch cyclic peptides (cyclopeptides).
Phylogenomics of 10,575 Genomes Reveals Evolutionary Proximity Between Domains Bacteria and Archaea
Nature Communications 10, 5477. (2019).
Optimizing sequencing protocols for leaderboard metagenomics by combining long and short reads
As metagenomic studies move to increasing numbers of samples, communities like the human gut may benefit more from the assembly of abundant microbes in many samples, rather than the exhaustive assembly of fewer samples.
Evaluating Metagenomic Prediction of the Metaproteome in a 4.5-Year Study of a Patient with Crohn’s Disease
mSystems 4:e00337-18. (2019).
Microbiome 101: Studying, Analyzing, and Interpreting Gut Microbiome Data for Clinicians
Clinical Gastroenterology and Hepatology 17, 218-230. (2019).
Extracting Insights On The Dynamic Health-Disease Transitions In The Human Gut Microbiome
Smarr, Larry, Marc Jaffrey, Michael Dushkoff, Brynn Taylor, Pilar Ackerman, Mehrdad Yezdani, and Weizhong Li. "EXTRACTING INSIGHTS ON THE DYNAMIC HEALTH-DISEASE TRANSITIONS IN THE HUMAN GUT MICROBIOME." (2018).
Metagenomics-Based, Strain-Level Analysis of Escherichia coli From a Time-Series of Microbiome Samples From a Crohn’s Disease Patient
Frontiers in Microbiology. Vol 9, article 2559. (2018).
Are microbiome studies ready for hypothesis-driven research?
Current Opinion Microbiology 44, 61-69. (2018).
Escherichia coli B2 Strains Prevalent in Inflammatory Bowel Disease Patients Have Distinct Metabolic Capabilities that Enable Colonization of Intestinal Mucosa
X. Fang, J. M. Monk, N. Mih, B. Du, A. Sastry, E. Kavvas, Y. Seif, L. Smarr, B. O. Palsson. BMC Systems Biology, 12, 66. (2018).
American Gut: an Open Platform for Citizen Science
The American Gut Consortium, Rob Knight. mSystems 3:e00031-18. (2018).
Creating a 3D microbial and chemical snapshot of a human habitat
Nature Scientific Reports, vol.8: 3669. (2018).
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.
Building an OptIPlanet collaboratory to support microbial metagenomics
Future Generation Computer Systems, Volume 25, Issue 2, pp. 124-131. February 2009.
CAMERA: A Community Resource for Metagenomics
R. Seshadri, SA Kravitz, L Smarr , Gilna P, M Frazier, PLoS Biol 5(3): e75.(2007).
Teaching Computers to Recognize Unhealthy Guts – SDSC’s ‘Gordon’ Supercomputer Assists in New Microbiome Study
January 18, 2017 - A new proof-of-concept study by researchers from the University of California San Diego has succeeded in training computers to “learn” what a healthy versus an unhealthy gut microbiome looks like based on its genetic makeup.
The Excrement Experiment – The New Yorker
But it was an inadvertent discovery in a stool analysis that led to Smarr's Crohn’s diagnosis and, eventually, to a new calling: as an evangelist for an impending medical revolution, “quantified health.”
From Quantified Self to Personalized Medicine – HPC Wire
November 6, 2014 - The University of Washington Computer Science and Engineering Distinguished Lecture series recently welcomed Calit2 luminary Larry Smarr to speak on a very interesting topic, bringing wellness into the digital age.Mind Brain Genome Microbiome: Conversation with Deepak Chopra
Deepak Chopra interviews Dr. Larry Smarr. We discussed everything from the origins of life, life in the universe, consciousness, mind brain genome, environment and the science of epigenetics. 04.23.2014.