The DOI matches its Crossref record; 46 of the 46 references it cites were found in a registry or an index.
IMG/M v.5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes
Open accessAbstract
The Integrated Microbial Genomes & Microbiomes system v.5.0 (IMG/M: https://img.jgi.doe.gov/m/) contains annotated datasets categorized into: archaea, bacteria, eukarya, plasmids, viruses, genome fragments, metagenomes, cell enrichments, single particle sorts, and metatranscriptomes. Source datasets include those generated by the DOE's Joint Genome Institute (JGI), submitted by external scientists, or collected from public sequence data archives such as NCBI. All submissions are typically processed through the IMG annotation pipeline and then loaded into the IMG data warehouse. IMG's web user interface provides a variety of analytical and visualization tools for comparative analysis of isolate genomes and metagenomes in IMG. IMG/M allows open access to all public genomes in the IMG data warehouse, while its expert review (ER) system (IMG/MER: https://img.jgi.doe.gov/mer/) allows registered users to access their private genomes and to store their private datasets in workspace for sharing and for further analysis. IMG/M data content has grown by 60% since the last report published in the 2017 NAR Database Issue. IMG/M v.5.0 has a new and more powerful genome search feature, new statistical tools, and supports metagenome binning.
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
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.
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
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
Discovering Statistics Using SPSS
Field, A. P., & Miles, J. N. V. (2000) · Medical Entomology and Zoology · Cited by 28,265
On a Test of Whether one of Two Random Variables is Stochastically Larger than the Other
Mann, H. B., & Whitney, D. R. (1947) · The Annals of Mathematical Statistics · doi:10.1214/aoms/1177730491 · Cited by 14,320
Prodigal: prokaryotic gene recognition and translation initiation site identification
Hyatt, D., Chen, G.-L., LoCascio, P. F., Land, M. L., Larimer, F. W., & Hauser, L. J. (2010) · BMC Bioinformatics · doi:10.1186/1471-2105-11-119 · Cited by 12,587
Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P., & Tyson, G. W. (2015) · Genome Research · doi:10.1101/gr.186072.114 · Cited by 12,496
InterProScan 5: genome-scale protein function classification
Jones, P., Binns, D., Chang, H.-Y., Fraser, M., Li, W., McAnulla, C., McWilliam, H., Maslen, J., Mitchell, A., Nuka, G., et al. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu031 · Cited by 9,301
KEGG as a reference resource for gene and protein annotation
Kanehisa, M., Sato, Y., Kawashima, M., Furumichi, M., & Tanabe, M. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1070 · Cited by 7,387
The Pfam protein families database: towards a more sustainable future
Finn, R. D., Coggill, P., Eberhardt, R. Y., Eddy, S. R., Mistry, J., Mitchell, A. L., Potter, S. C., Punta, M., Qureshi, M., Sangrador-Vegas, A., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkv1344 · Cited by 5,975
THE GENERALIZATION OF ‘STUDENT'S’ PROBLEM WHEN SEVERAL DIFFERENT POPULATION VARLANCES ARE INVOLVED
WELCH, B. L. (1947) · Biometrika · doi:10.1093/biomet/34.1-2.28 · Cited by 4,135
Infernal 1.1: 100-fold faster RNA homology searches
Nawrocki, E. P., & Eddy, S. R. (2013) · Bioinformatics · doi:10.1093/bioinformatics/btt509 · Cited by 3,591
Cited by
A unified catalog of 204,938 reference genomes from the human gut microbiome
Almeida, A., Nayfach, S., Boland, M., Strozzi, F., Beracochea, M., Shi, Z. J., Pollard, K. S., Sakharova, E., Parks, D. H., Hugenholtz, P., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-020-0603-3 · Cited by 1,367
Self-citationNew insights from uncultivated genomes of the global human gut microbiome
Nayfach, S., Shi, Z. J., Seshadri, R., Pollard, K. S., & Kyrpides, N. C. (2019) · Nature · doi:10.1038/s41586-019-1058-x · Cited by 737
Self-citationHuman gut bacteria produce ΤΗ17-modulating bile acid metabolites
Paik, D., Yao, L., Zhang, Y., Bae, S., D’Agostino, G. D., Zhang, M., Kim, E., Franzosa, E. A., Avila-Pacheco, J., Bisanz, J. E., et al. (2022) · Nature · doi:10.1038/s41586-022-04480-z · Cited by 594
MGnify: the microbiome analysis resource in 2020
Mitchell, A. L., Almeida, A., Beracochea, M., Boland, M., Burgin, J., Cochrane, G., Crusoe, M. R., Kale, V., Potter, S. C., Richardson, L. J., et al. (2019) · Nucleic Acids Research · doi:10.1093/nar/gkz1035 · Cited by 562
The IMG/M data management and analysis system v.6.0: new tools and advanced capabilities
Chen, I.-M. A., Chu, K., Palaniappan, K., Ratner, A., Huang, J., Huntemann, M., Hajek, P., Ritter, S., Varghese, N., Seshadri, R., et al. (2021) · Nucleic Acids Research · doi:10.1093/nar/gkaa939 · Cited by 445
Self-citation
Metadata
- Authors
- Chen, I.-M. A., Chu, K., Palaniappan, K., Pillay, M., Ratner, A., Huang, J., Huntemann, M., Varghese, N., White, J. R., Seshadri, R., Smirnova, T., Kirton, E., Jungbluth, S. P., Woyke, T., Eloe-Fadrosh, E. A., Ivanova, N. N., & Kyrpides, N. C.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2018-10-05
- Volume
- 47
- Issue
- D1
- Pages
- D666-D677
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2895532240
- Cited by
- 835
- References
- 46
- FWCI
- 38.92
- Type
- journal article
- Language
- en
- Open access
- gold
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
How to cite
Cite CoChat for the checks on this page, and the paper for its own findings.
- This page
- CoChat. (2026). Citation check: IMG/M v.5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes. https://app.cochat.ai/papers/10.1093/nar/gky901
- The paper
- Chen, I.-M. A., Chu, K., Palaniappan, K., Pillay, M., Ratner, A., Huang, J., Huntemann, M., Varghese, N., White, J. R., Seshadri, R., Smirnova, T., Kirton, E., Jungbluth, S. P., Woyke, T., Eloe-Fadrosh, E. A., Ivanova, N. N., & Kyrpides, N. C. (2019). IMG/M v.5.0: an integrated data management and comparative analysis system for microbial genomes and microbiomes. Nucleic Acids Research. https://doi.org/10.1093/nar/gky901
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.