The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
dbCAN-seq: a database of carbohydrate-active enzyme (CAZyme) sequence and annotation
Open accessAbstract
Carbohydrate-active enzyme (CAZymes) are not only the most important enzymes for bioenergy and agricultural industries, but also very important for human health, in that human gut microbiota encode hundreds of CAZyme genes in their genomes for degrading various dietary and host carbohydrates. We have built an online database dbCAN-seq (http://cys.bios.niu.edu/dbCAN_seq) to provide pre-computed CAZyme sequence and annotation data for 5,349 bacterial genomes. Compared to the other CAZyme resources, dbCAN-seq has the following new features: (i) a convenient download page to allow batch download of all the sequence and annotation data; (ii) an annotation page for every CAZyme to provide the most comprehensive annotation data; (iii) a metadata page to organize the bacterial genomes according to species metadata such as disease, habitat, oxygen requirement, temperature, metabolism; (iv) a very fast tool to identify physically linked CAZyme gene clusters (CGCs) and (v) a powerful search function to allow fast and efficient data query. With these unique utilities, dbCAN-seq will become a valuable web resource for CAZyme research, with a focus complementary to dbCAN (automated CAZyme annotation server) and CAZy (CAZyme family classification and reference database).
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
SignalP 4.0: discriminating signal peptides from transmembrane regions
Petersen, T. N., Brunak, S., von Heijne, G., & Nielsen, H. (2011) · Nature Methods · doi:10.1038/nmeth.1701 · Cited by 8,847
The abundance and variety of carbohydrate-active enzymes in the human gut microbiota
Kaoutari, A. E., Armougom, F., Gordon, J. I., Raoult, D., & Henrissat, B. (2013) · Nature Reviews Microbiology · doi:10.1038/nrmicro3050 · Cited by 1,683
Global distribution and diversity of marine Verrucomicrobia
Freitas, S., Hatosy, S., Fuhrman, J. A., Huse, S. M., Mark Welch, D. B., Sogin, M. L., & Martiny, A. C. (2012) · The ISME Journal · doi:10.1038/ismej.2012.3 · Cited by 236
Cited by
Gut-microbiota-targeted diets modulate human immune status
Wastyk, H. C., Fragiadakis, G. K., Perelman, D., Dahan, D., Merrill, B. D., Yu, F. B., Topf, M., Gonzalez, C. G., Van Treuren, W., Han, S., et al. (2021) · Cell · doi:10.1016/j.cell.2021.06.019 · Cited by 1,385
Profiling the human intestinal environment under physiological conditions
Shalon, D., Culver, R. N., Grembi, J. A., Folz, J., Treit, P. V., Shi, H., Rosenberger, F. A., Dethlefsen, L., Meng, X., Yaffe, E., et al. (2023) · Nature · doi:10.1038/s41586-023-05989-7 · Cited by 484
Bai, Z., Zhang, N., Jin, Y., Chen, L., Mao, Y., Sun, L., Fang, F., Liu, Y., Han, M., & Li, G. (2023) · Frontiers in Cellular and Infection Microbiology · doi:10.3389/fcimb.2022.919701 · Cited by 29
Gut microbiota drives structural variation of exogenous probiotics to enhance colonization
Jiang, S., Huang, S., Zhang, Z., Ma, W., Han, Z., Song, Y., Huo, D., Cui, W., & Zhang, J. (2025) · Gut Microbes · doi:10.1080/19490976.2025.2503371 · Cited by 15
Akhtar, A., Lata, M., Sunsunwal, S., Yadav, A., LNU, K., Subramanian, S., & Ramya, T. N. C. (2023) · Communications Biology · doi:10.1038/s42003-023-04718-0 · Cited by 9
CAZyme3D: A Database of 3D Structures for Carbohydrate-active Enzymes
Siva Shanmugam, N. R., & Yin, Y. (2025) · Journal of Molecular Biology · doi:10.1016/j.jmb.2025.169001 · Cited by 8
Self-citationProtein Language Models Uncover Carbohydrate-Active Enzyme Function in Metagenomics
Thurimella, K., Mohamed, A. M. T., Graham, D. B., Owens, R. M., La Rosa, S. L., Plichta, D. R., Bacallado, S., & Xavier, R. J. (2023) · doi:10.1101/2023.10.23.563620 · Cited by 7
Bacteriocin gene-mediated ecological adaptation of Bifidobacterium breve in the adult human gut
Wang, J., Qian, X., Li, Q., Jin, Z., Liu, N., Zhao, J., Chen, W., Wang, S., & Tian, P. (2026) · Cell Genomics · doi:10.1016/j.xgen.2025.101106 · Cited by 5
Metadata
- Authors
- Huang, L., Zhang, H., Wu, P., Entwistle, S., Li, X., Yohe, T., Yi, H., Yang, Z., & Yin, Y.
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2017-10-09
- Volume
- 46
- Issue
- D1
- Pages
- D516-D521
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- OpenAlex
- W2761566426
- Cited by
- 323
- References
- 3
- FWCI
- 5.82
- 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
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.
