The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.
Moving pictures of the human microbiome
Open accessAbstract
BACKGROUND: Understanding the normal temporal variation in the human microbiome is critical to developing treatments for putative microbiome-related afflictions such as obesity, Crohn’s disease, inflammatory bowel disease and malnutrition. Sequencing and computational technologies, however, have been a limiting factor in performing dense time series analysis of the human microbiome. Here, we present the largest human microbiota time series analysis to date, covering two individuals at four body sites over 396 timepoints. RESULTS: We find that despite stable differences between body sites and individuals, there is pronounced variability in an individual’s microbiota across months, weeks and even days. Additionally, only a small fraction of the total taxa found within a single body site appear to be present across all time points, suggesting that no core temporal microbiome exists at high abundance (although some microbes may be present but drop below the detection threshold). Many more taxa appear to be persistent but non-permanent community members. CONCLUSIONS: DNA sequencing and computational advances described here provide the ability to go beyond infrequent snapshots of our human-associated microbial ecology to high-resolution assessments of temporal variations over protracted periods, within and between body habitats and individuals. This capacity will allow us to define normal variation and pathologic states, and assess responses to therapeutic interventions.
Overview
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Integrity signals
Registry
Cites
Statistics
Figures
![Figure 1 Principal coordinates analysis of unweighted UniFrac distances between samples. (a) Costello et al. [6] samples. (b) M3, F4 time series samples. (c) M3, F4 time series, PC1 versus time (days). Panels (a,b) and (c) show two independent principal coordinates analyses. To compare the Costello et al. 454 data (a) with the time series Illumina data (b), these data were generated in a single principal coordinates analysis of UniFrac distances at 500 sequences per sample. Panel (c) does not contain the 454 data, so makes use of the increased sampling depth possible on Illumina (evenly sampled to 5,000 sequences per sample for UniFrac calculations).](/paper-figures/601978f4a5f14dce850c1ad072f786d6/moving-pictures-of-the-human-microbiome-figure-1.jpg)
Verification
Claims the paper makes
The claims and statistics of this paper haven’t been checked yet.
Run the check — free, no account needed. It reads the open-access text and checks the sources it cites.
Claims other papers make about this one
Each is checked against this paper’s own text: does it say what the citing paper says it does?
The cited source says what the claim attributes to it.
In the citing paper
“the fine structure of the healthy microbiota seems to be unique to individuals; intra-individual differences across time are typically much smaller than differences between individuals (Caporaso et al., 2011;Costello et al., 2009).”
From The Microbiota-Gut-Brain Axis (2019) · cites this paper as Caporaso et al., 2011
Self-check
Percentages, sums and reported differences re-computed from the paper’s own numbers.
The self-check needs the paper’s full text.
Citations
Cites
Search and clustering orders of magnitude faster than BLAST
Edgar, R. C. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq461 · Cited by 21,098
A human gut microbial gene catalogue established by metagenomic sequencing
MetaHIT Consortium, Qin, J., Li, R., Raes, J., Arumugam, M., Burgdorf, K. S., Manichanh, C., Nielsen, T., Pons, N., Levenez, F., et al. (2010) · Nature · doi:10.1038/nature08821 · Cited by 11,624
Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB
DeSantis, T. Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E. L., Keller, K., Huber, T., Dalevi, D., Hu, P., & Andersen, G. L. (2006) · Applied and Environmental Microbiology · doi:10.1128/aem.03006-05 · Cited by 10,891
Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample
Caporaso, J. G., Lauber, C. L., Walters, W. A., Berg-Lyons, D., Lozupone, C., Turnbaugh, P. J., Fierer, N., & Knight, R. D. (2010) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1000080107 · Cited by 9,944
Self-citationDiversity of the Human Intestinal Microbial Flora
Eckburg, P. B., Bik, E. M., Bernstein, C. N., Purdom, E., Dethlefsen, L., Sargent, M., Gill, S. R., Nelson, K. E., & Relman, D. A. (2005) · Science · doi:10.1126/science.1110591 · Cited by 7,913
A core gut microbiome in obese and lean twins
Turnbaugh, P. J., Hamady, M., Yatsunenko, T., Cantarel, B. L., Duncan, A., Ley, R. E., Sogin, M. L., Jones, W. J., Roe, B. A., Affourtit, J. P., et al. (2009) · Nature · doi:10.1038/nature07540 · Cited by 7,823
Self-citationVaginal microbiome of reproductive-age women
Ravel, J., Gajer, P., Abdo, Z., Schneider, G. M., Koenig, S. S. K., McCulle, S. L., Karlebach, S., Gorle, R., Russell, J., Tacket, C. O., et al. (2011) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.1002611107 · Cited by 4,254
Self-citationBacterial Community Variation in Human Body Habitats Across Space and Time
Costello, E. K., Lauber, C. L., Hamady, M., Fierer, N., Gordon, J. I., & Knight, R. (2009) · Science · doi:10.1126/science.1177486 · Cited by 3,231
Self-citationThe Effect of Diet on the Human Gut Microbiome: A Metagenomic Analysis in Humanized Gnotobiotic Mice
Turnbaugh, P. J., Ridaura, V. K., Faith, J. J., Rey, F. E., Knight, R., & Gordon, J. I. (2009) · Science Translational Medicine · doi:10.1126/scitranslmed.3000322 · Cited by 3,058 · cited 2×
“…together, our observations paint a picture of a human microbiome that is highly variable over time (Figures 2 and 3; Additional files 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15), but from which stable patterns of similarities and differences among body habitats and individuals emerge (Figure…”
BackgroundSelf-citationDevelopment of the Human Infant Intestinal Microbiota
Palmer, C., Bik, E. M., DiGiulio, D. B., Relman, D. A., & Brown, P. O. (2007) · PLoS Biology · doi:10.1371/journal.pbio.0050177 · Cited by 2,877
Cited by
Sorted by citations
Items 901–1,000 of 1,000
Starvation Influences the Microbiota in the Stomach of the Corallivorous Crown-of-Thorns Starfish
Zhang, Y., Lai, F., Yang, L., Dai, L., Su, N. Y., Hu, J., Chen, H., Gao, Q., Zheng, F., & Chen, C. Q. (2025) · Biology · doi:10.3390/biology14081102 · Cited by 2
KADAIF: an anomaly detection method for complex microbiome data
Peleg, O., Raytan, M., & Borenstein, E. (2025) · Bioinformatics · doi:10.1093/bioinformatics/btaf520 · Cited by 2
Fixation and extinction in time-fluctuating spatially structured metapopulations
Asker, M., Swailem, M., Täuber, U. C., & Mobilia, M. (2025) · Physical Review Research · doi:10.1103/6w4h-8xvk · Cited by 2
The eco-evolutionary assembly of complex communities with multiple interaction types
Araujo, G., & Lurgi, M. (2026) · Nature Communications · doi:10.1038/s41467-026-70117-8 · Cited by 2
Die Bedeutung des humanen Mikrobioms für die menschliche Gesundheit
Schloter, M., Kostrić, M., Schöler, A., Treichel, N. S., Krauss‐Etschmann, S., & Berg, G. (2015) · BIOspektrum · doi:10.1007/s12268-015-0534-6 · Cited by 2
Methods for Microbiota Analysis: Sample Collection and Laboratory Methods
Ibrahim, S. M., & Belheouane, M. (2018) · Springer eBooks · doi:10.1007/978-3-319-79026-8_2 · Cited by 2
Zheng, T., Gao, Y., Xu, Y., Chen, Z., Wang, X., Liu, J., & Liu, G. (2020) · Inflammation · doi:10.1007/s10753-020-01372-0 · Cited by 3
RSim: A reference-based normalization method via rank similarity
Yuan, B., & Wang, S. (2023) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1011447 · Cited by 4
Alterations in microbiome of COVID-19 patients and its impact on forensic investigations
Mir, T. U. G., Manhas, S., Wani, A. K., Akhtar, N., Shukla, S., & Prakash, A. (2023) · Science & Justice · doi:10.1016/j.scijus.2023.12.002 · Cited by 2
Brauer, V. S., Voskuhl, L., Mohammadian, S., Pannekens, M., Haque, S., & Meckenstock, R. U. (2024) · FEMS Microbiology Ecology · doi:10.1093/femsec/fiae074 · Cited by 2
SpotVerse: Optimizing Bioinformatics Workflows with Multi-Region Spot Instances in Galaxy and Beyond
Son, M., Akbulut, G. G., & Kandemir, M. (2024) · International Middleware Conference · doi:10.1145/3652892.3700750 · Cited by 6
Quinteros-Urquieta, C., Francois, J. P., Aguilar‐Muñoz, P., & Molina, V. (2024) · Microorganisms · doi:10.3390/microorganisms12122487 · Cited by 2
Critical behavior of a phase transition in the dynamics of interacting populations
de Pirey, T. A., & Bunin, G. (2025) · SciPost Physics · doi:10.21468/scipostphys.18.2.051 · Cited by 2
Resilience of a stochastic generalized Lotka–Volterra model for microbiome studies
Phan, T. A., Ridenhour, B. J., & Remien, C. H. (2025) · Mathematical Biosciences & Engineering · doi:10.3934/mbe.2025056 · Cited by 2
Microbiote, ce qu’il faut savoir
Sokol, H. (2014) · Côlon & Rectum · doi:10.1007/s11725-014-0536-4 · Cited by 2
Report of the 13th Genomic Standards Consortium Meeting, Shenzhen, China, March 4–7, 2012.
Gilbert, J. A., Bào, Y., Wang, H., Sansone, S., Edmunds, S., Morrison, N., Meyer, F., Schriml, L. M., Davies, N., Sterk, P., et al. (2012) · Standards in Genomic Sciences · doi:10.4056/sigs.2876184 · Cited by 2
Gut Microbiota Pattern of Centenarians
Wu, L. H., Zinellu, A., Milanesi, L., Rubino, S., Kelvin, D. J., & Carru, C. (2019) · Springer eBooks · doi:10.1007/978-3-030-20762-5_9 · Cited by 2
Archaea and their potential pathogenicity in human and animal diseases.
KUMONDOROVA, A., & İkiz, S. (2019) · Journal of Istanbul Veterinary Sciences · doi:10.30704/http-www-jivs-net.641538 · Cited by 2
Amieva‐Balmori, M., García-Mazcorro, J. F., Martínez-Conejo, A., Hernández-Ramírez, G. A., García‐Zermeño, K. R., Rodríguez-Aguilera, O., Aja-Cadena, M., Cortes-Barradas, M., Quigley, E. M. M., & Remes-Troche, J. M. (2022) · Revista de Gastroenterología de México (English Edition) · doi:10.1016/j.rgmxen.2022.06.014 · Cited by 2
Campbell, L. J., Castillo, N. A., Dunn, C. D., Bose, S. M., Perez, A. U., Schmitter-Soto, J. J., Mejri, S., Boucek, R. E., Santos, R. O., Adams, A. J., et al. (2023) · Environmental Biology of Fishes · doi:10.1007/s10641-023-01462-6 · Cited by 2
Ai, D., Chen, L., Xie, J., Cheng, L., Zhang, F., Luan, Y., Li, Y., Hou, S., Sun, F., & Xia, L. C. (2023) · Briefings in Bioinformatics · doi:10.1093/bib/bbad390 · Cited by 3
Diet and Gut Microbiota in Human Health
Hemalatha, R. (2016) · Revista de Fomento Social · doi:10.16943/ptinsa/2016/48878 · Cited by 2
Zhang, F., Shan, A., & Luan, Y. (2018) · Statistical Applications in Genetics and Molecular Biology · doi:10.1515/sagmb-2018-0019 · Cited by 2
Microbiota in Pouchitis and De Novo Crohn’s Disease of the Ileal Pouch
Coffey, J. C., & Bolger, J. C. (2018) · Elsevier eBooks · doi:10.1016/b978-0-12-809402-0.00010-1 · Cited by 2
Microbiota perinatal: Revisión de su importancia en la salud del recién nacido
(2020) · Archivos Argentinos de Pediatria · doi:10.5546/aap.2020.e265 · Cited by 2
Omics for Forensic and Post-Mortem Microbiology
Fernández-Rodríguez, A., Gónzález‐Candelas, F., & Arora, N. (2021) · Springer eBooks · doi:10.1007/978-3-030-62155-1_12 · Cited by 2
The oral microbiota as part of the human microbiota – links to general health
Belstrøm, D. (2020) · Den norske tannlegeforenings Tidende · doi:10.56373/2020-2-5 · Cited by 2
Tikhonov, M., & Wingreen, N. S. (2013) · arXiv (Cornell University) · Cited by 2
Consistent, comprehensive and computationally efficient OTU definitionsPreprint
Rideout, J. R., He, Y., Navas-Molina, J. A., Walters, W. A., Ursell, L. K., Gibbons, S. M., Chase, J., McDonald, D. T., Gonzalez, A., Robbins‐Pianka, A., et al. (2014) · doi:10.7287/peerj.preprints.411v2 · Cited by 2
Self-citationModulation of cellular innate immune responses by lactobacilli
Karlsson, M. (2012) · Örebro University Library (Örebro University) · Cited by 2
Robust Parameter Estimation for Biological Systems: A Study on the Dynamics of Microbial CommunitiesPreprint
Chung, M., Krueger, J., & Pop, M. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1509.06926 · Cited by 3
Deep characterization of Escherichia coli in a cohort of mothers and their infants
de Muinck, & Jacques, É. (2013) · Cited by 2
Mechanisms of Dysbiosis in the Inflamed Gut
Winter, S. (2016) · Wiley eBooks · doi:10.1002/9783527682386.ch5 · Cited by 1
An introduction to microbial dysbiosis
Curtis, M. (2016) · Wiley eBooks · doi:10.1002/9781118982907.ch2 · Cited by 2
Pearson, T., Caporaso, J. G., Yellowhair, M., Bokulich, N. A., Roe, D. J., Wertheim, B. C., Linhart, M., Martinez, J. A., Bilagody, C., Hornstra, H., et al. (2017) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/237495 · Cited by 2
Self-citationStronger connectivity of the resident gut microbiome lends resistance to invading bacteriaPreprint
Herren, C. M., & Baym, M. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/261750 · Cited by 2
Gans, M., Custer, G., van Diepen, L. T. A., & Buerkle, C. A. (2021) · doi:10.22541/au.162319124.47034276/v1 · Cited by 2
Synchronous seasonality in the gut microbiota of wild wood mouse populationsPreprint
Marsh, K. J., Raulo, A., Brouard, M. J., Troitsky, T. S., English, H. M., Allen, B. E., Raval, R., Webster, J. P., & Knowles, S. C. L. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.10.15.464528 · Cited by 2
(2013) · Environmental Microbiology Reports · doi:10.1111/1758-2229.12021 · Cited by 2
Skin Microbiota and Attractiveness to Mosquitoes
Verhulst, N. O., & Takken, W. (2015) · Springer eBooks · doi:10.1007/978-1-4899-7475-4_409 · Cited by 2
Functional redundancy enables emergent metabolic dynamics in marine microbiomesPreprint
González-Motos, S., Montiel, L., Balagué, V., Bouget, F., Massana, R., Gasol, J. M., González, J. M., Galand, P. E., & Logares, R. (2025) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2025.08.12.669827 · Cited by 2
Modulating T Follicular Cells In Vivo Enhances Antigen-Specific Humoral Immunity
Pagan, J. D., Vlamakis, H. C., Gaca, A. O., Xavier, R. J., & Anthony, R. M. (2021) · The Journal of Immunology · doi:10.4049/jimmunol.2001434 · Cited by 2
Gut microbiota and endometriosis
Yoshino, O., Ono, Y., & Hiraoka, T. (2021) · Elsevier eBooks · doi:10.1016/b978-0-12-820661-4.00011-x · Cited by 1
Manus, M. B., Lucore, J. M., Kuthyar, S., Moy, M. R., Sardaro, M. L. S., & Amato, K. R. (2024) · American Journal of Biological Anthropology · doi:10.1002/ajpa.25020 · Cited by 1
Repopulation of the gut microbiota after a screening colonoscopy
Ghouri, Y. A., Ericsson, A. C., Anderson, J. M., George, J., Parks, E. J., & Anguah, K. O.-B. (2025) · PLoS ONE · doi:10.1371/journal.pone.0320712 · Cited by 4
Tokamani, M., Liakopoulos, P., Tegopoulos, K., Zigkou, A.-M., Triantaphyllidis, G., Kamidis, N., Grigoriou, M. E., Sandaltzopoulos, R., & Kolovos, P. (2025) · Microorganisms · doi:10.3390/microorganisms13102373 · Cited by 1
Longitudinal changes in gut microbiota across reproductive states in wild baboons
Southworth, C. A., Barrios, L., Dasari, M. R., Gesquiere, L. R., Gilbert, J. A., Alberts, S. C., Tung, J., & Archie, E. A. (2026) · Microbiome · doi:10.1186/s40168-026-02494-7 · Cited by 2
Meireles, I. D. M., Costa, B. T. A., Lobato, H. C., Lobato, H. C., Araújo, I. C. S., & Lara, L. J. C. (2026) · Revista Brasileira de Zootecnia · doi:10.37496/rbz5520250078 · Cited by 1
Song, C.-H., Choi, Y., Kim, N., Ha, S., Park, J. H., Lee, H.-K., Shin, C. M., & Ahn, S. (2026) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2026.1848437 · Cited by 1
Dutta, S., Dutta, T. K., Nanda, P. K., Dhar, P., Das, A. K., & Bhunia, A. K. (2026) · Probiotics and Antimicrobial Proteins · doi:10.1007/s12602-026-11136-1 · Cited by 2
Technology Advancement Enabling the Link of Gut Microbiota with Obesity and Metabolic Disorder
YUSOF, H., Aazmi, M. S., Abdullah, I. N., Teh, L. K., Ahmad, A., Omar, M., Rahman, T. H. A., & Salleh, M. Z. (2015) · Jurnal Sains Kesihatan Malaysia · doi:10.17576/jskm-2015-1301-10 · Cited by 1
GPU-Meta-Storms: Computing the similarities among massive microbial communities using GPU
Su, X., Wang, X., Xu, J., & Ning, K. (2013) · IEEE International Conference on Systems Biology · doi:10.1109/isb.2013.6623796 · Cited by 1
Feature subset selection for inferring relative importance of taxonomy
Ditzler, G., & ROSEN, G. L. (2014) · ACM International Conference on Bioinformatics, Computational Biology, and Health Informatics (ACM-BCB) · doi:10.1145/2649387.2660824 · Cited by 1
Application of Meta‐Mesh on the analysis of microbial communities from human associated‐habitats
Su, X., Wang, X., Jing, G., Huang, S. W., Xu, J., & Ning, K. (2015) · Quantitative Biology · doi:10.1007/s40484-015-0040-3 · Cited by 1
CHANGES IN THE HUMAN SKIN MICROBIOME OVER ONE YEAR’S TIME
Hyman (2012) · Current Research in Microbiology · doi:10.3844/ajmsp.2012.18.30 · Cited by 1
[Meta-Mesh: metagenomic data analysis system].
Su, X., Song, B., Wang, X., Ma, X., Xu, J., & Ning, K. (2014) · PubMed · Cited by 1
Methods for Microbiome Analysis
Ibrahim, K. S., & Kumar, N. S. (2017) · Translational medicine research · doi:10.1007/978-94-024-1045-7_12 · Cited by 1
Paulino, L. C. (2017) · Springer eBooks · doi:10.1007/978-3-319-59997-7_5 · Cited by 1
The Emerging Role of Microbiome–Gut–Brain Axis in Functional Gastrointestinal Disorders
Skonieczna‐Żydecka, K., Łoniewski, I., Koulaouzidis, A., & Marlicz, W. M. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-815249-2.00026-9 · Cited by 1
Exploring Computational Inference of Microbial Interactions and their Dynamics
Vidanaarachchi, R., Shaw, M. E., & Halgamuge, S. K. (2019) · IEEE International Conference on Industrial and Information Systems (ICIIS) · doi:10.1109/iciis47346.2019.9063336 · Cited by 1
An Introduction to Microbial Forensics
Aeri, R., Arora, J. S., Kapoor, P., & Sharma, A. D. (2020) · Springer eBooks · doi:10.1007/978-981-15-4099-8_21 · Cited by 1
The Gut Microbiome in Serious Mental Illnesses
Tzavellas, E., Logotheti, M., & Stefanis, N. C. (2021) · The microbiomes of humans, animals, plants, and the environment · doi:10.1007/978-3-030-59642-2_8 · Cited by 1
de Vos, W. M. (2014) · Apple Academic Press eBooks · doi:10.1201/b17254-20 · Cited by 1
Amieva‐Balmori, M., García-Mazcorro, J. F., Martínez-Conejo, A., Hernández-Ramírez, G. A., García‐Zermeño, K. R., Rodríguez-Aguilera, O., Aja-Cadena, M., Cortes-Barradas, M., Quigley, E. M. M., & Remes-Troche, J. M. (2022) · Revista de Gastroenterología de México · doi:10.1016/j.rgmx.2022.04.005 · Cited by 1
Nathan, M. K., Jasni, A. S., Zakariah, S. Z., Jamaluddin, T. Z. M. T., Isa, M. M., & Ibrahim, R. (2023) · Journal of Medical Microbiology · doi:10.1099/jmm.0.001732 · Cited by 1
Procedures for sampling of small and larger samples of microbiome
Adetunji, J. B., Michael, O. S., Adetunji, C. O., Ajayi, O. O., & Ogundolie, F. A. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-91190-0.00003-5 · Cited by 1
Adetunji, C. O., Michael, O. S., Ajayi, O. O., Ogundolie, F. A., Adetunji, J. B., & Oyewole, O. A. (2024) · Elsevier eBooks · doi:10.1016/b978-0-323-91190-0.00001-1 · Cited by 1
Behavioral Profile and Gut Microbiota Composition in Rats with Different Nervous System Excitability
Shalaginova, I., Katserov, D., Ensh, K. O., Budenkova, E., Pribyshina, A. K., & Dyuzhikova, N. (2025) · Journal of Evolutionary Biochemistry and Physiology · doi:10.1134/s0022093025030068 · Cited by 1
The skin microbiome, new knowledge, atopic dermatitis
Zelenková, H. (2016) · Pediatrie pro praxi · doi:10.36290/ped.2016.066 · Cited by 1
Nascimento, M. M. (2019) · Elsevier eBooks · doi:10.1016/b978-0-12-815249-2.00009-9 · Cited by 1
Herren, C. M. (2019) · Applied and Environmental Microbiology · doi:10.1128/aem.01099-19 · Cited by 1
Gut Microbiome and Alzheimer’s Disease
Seol, K., Kim, H.-W., Yoo, J., Yun, J.-H., Oh, M., & Ham, J.-S. (2021) · Journal of Dairy Science and Biotechnology · doi:10.22424/jdsb.2021.39.3.94 · Cited by 1
Efficient Approximation of Statistical Significance in Local Trend Analysis of Dependent Time Series
Shan, A., Zhang, F., & Luan, Y. (2022) · Frontiers in Genetics · doi:10.3389/fgene.2022.729011 · Cited by 1
Statistical models for large-scale comparative metagenome analysis
Aßhauer, K. P. (2015) · eDiss (Georg-August-Universität Göttingen) · doi:10.53846/goediss-5033 · Cited by 1
Habitat Fluctuations Drive Species Covariation in the Human MicrobiotaPreprint
Fisher, C. K., Mora, T., & Walczak, A. M. (2015) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/028209 · Cited by 1
Using Rule Induction to Elucidate Co-Occurrence Patterns in Microbial Data
Thurimella, K. (2013) · CU Scholar (University of Colorado Boulder) · Cited by 1
Rzotkiewicz, A. (2016) · Michigan State University Libraries · doi:10.25335/j0e4-7g79 · Cited by 1
Li, C., Tucker‐Kellogg, L., & Nagarajan, N. (2018) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/288803 · Cited by 1
Human identification through analysis of the salivary microbiome: proof of principle
Leake, S. L. (2014) · IRIS · Cited by 1
Zhang, R. (2017) · Louisiana State University · doi:10.31390/gradschool_dissertations.4272 · Cited by 1
Species-level microbial sequence classification is improved by source-environment informationPreprint
Kaehler, B. D., Bokulich, N. A., McDonald, D., Knight, R. D., Caporaso, J. G., & Huttley, G. A. (2019) · Repository for Publications and Research Data (ETH Zurich) · doi:10.3929/ethz-b-000431207 · Cited by 1
Self-citationEcological forces shaping gut microbiota in wild animal populations
Ren, T. (2016) · doi:10.18130/v3x30q · Cited by 1
Synergistic Inhibitory Effect of the Gut Microbiome and Lithocholic Acid on Liver FibrosisPreprint
Shao, J., Ge, T., Chen, S., & Chen, Z. (2021) · Research Square · doi:10.21203/rs.3.rs-170652/v1 · Cited by 1
Bich, V. T. N., Hai, H. B., Galazzo, G., Vu, D. T. V., Oomen, M., Minh, T. N. N., Hoang, T. H., van Doorn, H. R., Wertheim, H. F. L., & Penders, J. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.02.23.432416 · Cited by 1
Complexity-stability relationship in empirical microbial ecosystemsPreprint
Yonatan, Y., Amit, G., Friedman, J., & Bashan, A. (2021) · bioRxiv (Cold Spring Harbor Laboratory) · doi:10.1101/2021.07.29.454345 · Cited by 1
I Seven International Medical and Nursing Congress
Coelho, P., Rodrigues, F., & Gouveia, A. (2022) · doi:10.56238/sevenmedicalnursing2022 · Cited by 1
Social and environmental predictors of gut microbiome age in wild baboonsPreprint
Dasari, M. R., Roche, K. E., Jansen, D., Anderson, J. A., Alberts, S. C., Tung, J., Gilbert, J. A., Blekhman, R., Mukherjee, S., & Archie, E. A. (2024) · eLife · doi:10.7554/elife.102166.1 · Cited by 1
Exploring the nature and diversity of microorganisms in healthcare and educational settings
D’Arcy, N. (2014) · UCL Discovery (University College London) · Cited by 1
Meeting report for the 1st skin microbiota workshop, boulder, CO October 15-16 2012
Gilbert, J. A., Ball, M. P., Blainey, P. C., Blaser, M. J., Bohannan, B. J. M., Bateman, A. C., Bunge, J., Domínguez-Bello, M. G., Epstein, S. S., Fierer, N., et al. (2014) · Standards in Genomic Sciences · doi:10.1186/1944-3277-9-13
Self-citationSkin Microbiota and Attractiveness to Mosquitoes
Verhulst, N. O., & Takken, W. (2013) · Springer eBooks · doi:10.1007/978-1-4614-6418-1_409-1
Variable Selection to Improve Classification of Metagenomes
Ditzler, G., Lan, Y., Bouchot, J.-L., & ROSEN, G. L. (2013) · Springer eBooks · doi:10.1007/978-1-4614-6418-1_364-4
Determining significance in metagenomic samples
Ditzler, G., Robi Polikar, A., & ROSEN, G. L. (2012) · IEEE Annual Northeast Bioengineering Conference (NEBEC) · doi:10.1109/nebc.2012.6207004
Maretty, L., Sibbesen, J. A., & Krogh, A. (2014)
McCord, A. I., Chapman, C. A., Weny, G., Tumukunde, A., Hyeroba, D., Klotz, K., Koblings, A. S., Cregger, M. A., White, B. A., Leigh, S. R., et al. (2014)
Supervised Non-negative Matrix Factorization for Analysis of Microbiome Data
Cai, Y. (2014) · DalSpace (Dalhousie University)
Vicente, A. D. (2013) · Dialnet (Universidad de la Rioja)
The obesogenic effects of high-fat diets are influenced by both protein source and amount
Bjelland, S. (2013) · NORA - Norwegian Open Research Archives
YUSOF, H., Aazmi, M. S., Abdullah, I. N., Teh, L. K., Ahmad, A., Omar, M., Rahman, T. H. A., & Salleh, M. Z. (2015)
Walters, W. A. (2014) · CU Scholar (University of Colorado Boulder)
Metadata
- Authors
- Caporaso, J. G., Lauber, C. L., Costello, E. K., Berg-Lyons, D., Gonzalez, A., Stombaugh, J., Knights, D., Gajer, P., Ravel, J., Fierer, N., Gordon, J. I., & Knight, R.
- Affiliations
- University of Colorado Boulder (US)
- Cooperative Institute for Research in Environmental Sciences (US)
- Stanford Medicine (US)
- University of Maryland, Baltimore (US)
- Washington University in St. Louis (US)
- Howard Hughes Medical Institute (US)
- Corresponding author
- Knight, Rob
- ORCID
- Venue
- Genome Biology
- Published
- 2011-05-30
- Volume
- 12
- Issue
- 5
- Pages
- R50-R50
- ISSN
- 1465-6906 (ISSN-L)
- 1474-760X
- PMC
- PMC3271711
- OpenAlex
- W2126218947
- Cited by
- 1,138
- References
- 21
- Citations by year
- 2026: 25 · 2025: 50 · 2024: 69 · 2023: 80 · 2022: 68 · 2021: 88 · 2020: 102 · 2019: 93 · 2018: 83 · 2017: 84 · 2016: 78 · 2015: 79 · 2014: 78 · 2013: 82 · 2012: 61
- FWCI
- 30.93
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Locations
- Genome biology (publishedVersion, cc-by)
- Europe PMC (PubMed Central) (publishedVersion, cc-by)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Digital Commons@Becker (Washington University School of Medicine) (submittedVersion)
- Funders
- Howard Hughes Medical Institute
- Bill and Melinda Gates Foundation
- Crohn's and Colitis Foundation of America
- Amazon Web Services
- Crohn's and Colitis Foundation
- National Institutes of Health (5u01ai070921-07, DK078669)
- National Human Genome Research Institute (R01HG004872, HG004872, HG004872-02S1)
- National Institute of Allergy and Infectious Diseases (AI070921, AI083264, UH2AI083264)
- National Institute of Diabetes and Digestive and Kidney Diseases (DK078669, P01DK078669)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Gut microbiota and health
- Physical Sciences › Environmental Science › Ecology › Microbial Community Ecology and Physiology
- Health Sciences › Dentistry › Periodontics › Oral microbiology and periodontitis research
- Keywords
- human microbiome, temporal variation, core microbiome, microbial community dynamics, body site differences, interindividual variability, microbiome sequencing
- MeSH terms
- Bacteria, Computer Simulation, Humans, Obesity, Organ Specificity, RNA, Ribosomal, 16S, Seasons, Time Factors, Inflammatory Bowel Diseases, Genomics, Gastrointestinal Tract, Metagenome, High-Throughput Nucleotide Sequencing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
Are you an author, or do you see a problem with this page? Request a review
