The DOI matches its Crossref record; 3 of the 3 references it cites were found in a registry or an index.
Binning metagenomic contigs by coverage and composition
Open accessOverview
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
Structure, function and diversity of the healthy human microbiome
The Human Microbiome Project Consortium (2012) · Nature · doi:10.1038/nature11234 · Cited by 11,726
Community structure and metabolism through reconstruction of microbial genomes from the environment
Tyson, G. W., Chapman, J., Hugenholtz, P., Allen, E. E., Ram, R. J., Richardson, P. M., Solovyev, V. V., Rubin, E. M., Rokhsar, D. S., & Banfield, J. F. (2004) · Nature · doi:10.1038/nature02340 · Cited by 2,417
Toward Automatic Reconstruction of a Highly Resolved Tree of Life
Ciccarelli, F. D., Doerks, T., von Mering, C., Creevey, C. J., Snel, B., & Bork, P. (2006) · Science · doi:10.1126/science.1123061 · Cited by 1,663
Research works printed but not linked: 16
- Herlemann, D.P. et al. MBio 4, e00569–e00512 (2013). · DOI · Paper page
- Sharon, I. & Banfield, J.F. Science 342, 1057–1058 (2013). · DOI · Paper page
- Kislyuk, A., Bhatnagar, S., Dushoff, J. & Weitz, J.S. BMC Bioinformatics 10, 316 (2009). · DOI
- Strous, M., Kraft, B., Bisdorf, R. & Tegetmeyer, H. Front. Microbiol. 3, 410 (2012). · DOI · Paper page
- Chatterji, S., Yamazaki, I., Bai, Z. & Eisen, J.A. in Res. Comput. Mol. Biol. (eds. Vingron, M. & Wong, L.) 17–28 (Springer, 2008). · DOI
- Kelley, D.R. & Salzberg, S.L. BMC Bioinformatics 11, 544 (2010). · DOI
- Sharon, I. et al. Genome Res. 23, 111–120 (2013). · DOI · Paper page
- Albertsen, M. et al. Nat. Biotechnol. 31, 533–538 (2013). · DOI · Paper page
- Corduneanu, A. & Bishop, C.M. in Artif. Intell. Stat. 2001 (eds. Jaakkola, T. & Richardson, T.) 27–34 (Morgan Kaufmann, 2001).
- Sandberg, R. et al. Genome Res. 11, 1404–1409 (2001). · DOI · Paper page
- Dick, G.J. et al. Genome Biol. 10, R85 (2009). · DOI · Paper page
- Loman, N.J. et al. J. Am. Med. Assoc. 309, 1502–1510 (2013). · DOI · Paper page
- Asahara, T. et al. Infect. Immun. 72, 2240–2247 (2004). · DOI · Paper page
- Pell, J. et al. Proc. Natl. Acad. Sci. USA 109, 13272–13277 (2012). · DOI · Paper page
- Boisvert, S., Raymond, F., Godzaridis, E., Laviolette, F. & Corbeil, J. Genome Biol. 13, R122 (2012). · DOI · Paper page
- Tatusov, R.L., Koonin, E.V. & Lipman, D.J. Science 278, 631–637 (1997). · DOI · Paper page
Cited by
MetaWRAP—a flexible pipeline for genome-resolved metagenomic data analysis
Uritskiy, G. V., DiRuggiero, J., & Taylor, J. (2018) · Microbiome · doi:10.1186/s40168-018-0541-1 · Cited by 2,642
Shotgun metagenomics, from sampling to analysis
Quince, C., Walker, A. W., Simpson, J. T., Loman, N. J., & Segata, N. (2017) · Nature Biotechnology · doi:10.1038/nbt.3935 · Cited by 2,202
Self-citationLi, D., Luo, R., Liu, C.-M., Leung, C.-M., Ting, H.-F., Sadakane, K., Yamashita, H., & Lam, T.-W. (2016) · Methods · doi:10.1016/j.ymeth.2016.02.020 · Cited by 2,079
Best practices for analysing microbiomes
Knight, R., Vrbanac, A., Taylor, B. C., Aksenov, A., Callewaert, C., Debelius, J., Gonzalez, A., Kosciolek, T., McCall, L.-I., McDonald, D., et al. (2018) · Nature Reviews Microbiology · doi:10.1038/s41579-018-0029-9 · Cited by 2,030
(2015) · doi:10.7717/peerj.1165 · Cited by 1,960
Anvi’o: an advanced analysis and visualization platform for ‘omics data
Eren, A. M., Esen, Ö. C., Quince, C., Vineis, J. H., Morrison, H. G., Sogin, M. L., & Delmont, T. O. (2015) · PeerJ · doi:10.7717/peerj.1319 · Cited by 1,887
Self-citationPasolli, E., Asnicar, F., Manara, S., Zolfo, M., Karcher, N., Armanini, F., Beghini, F., Manghi, P., Tett, A., Ghensi, P., et al. (2019) · Cell · doi:10.1016/j.cell.2019.01.001 · Cited by 1,591
Self-citationRecovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy
(2017) · doi:10.1038/s41564-018-0171-1 · Cited by 1,742
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
Asgard archaea illuminate the origin of eukaryotic cellular complexity
Zaremba-Niedzwiedzka, K., Caceres, E. F., Saw, J. H., Bäckström, D., Juzokaite, L., Vancaester, E., Seitz, K. W., Anantharaman, K., Starnawski, P., Kjeldsen, K. U., et al. (2017) · Nature · doi:10.1038/nature21031 · Cited by 1,226
Microbial strain-level population structure and genetic diversity from metagenomes
Truong, D. T., Tett, A., Pasolli, E., Huttenhower, C., & Segata, N. (2017) · Genome Research · doi:10.1101/gr.216242.116 · Cited by 839
Critical Assessment of Metagenome Interpretation—a benchmark of metagenomics software
Sczyrba, A., Hofmann, P., Belmann, P., Koslicki, D., Janssen, S., Dröge, J., Gregor, I., Majda, S., Fiedler, J., Dahms, E., et al. (2017) · Nature Methods · doi:10.1038/nmeth.4458 · Cited by 870
Self-citationThe microbiome of uncontacted Amerindians
Clemente, J. C., Pehrsson, E. C., Blaser, M. J., Sandhu, K., Gao, Z., Wang, B., Magris, M., Hidalgo, G., Contreras, M., Noya-Alarcón, Ó., et al. (2015) · Science Advances · doi:10.1126/sciadv.1500183 · Cited by 851
New 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
Improved metagenome binning and assembly using deep variational autoencoders
Nissen, J. N., Johansen, J., Allesøe, R. L., Sønderby, C. K., Armenteros, J. J. A., Grønbech, C. H., Jensen, L. J., Nielsen, H. B., Petersen, T. N., Winther, O., et al. (2021) · Nature Biotechnology · doi:10.1038/s41587-020-00777-4 · Cited by 649
Benchmarking Metagenomics Tools for Taxonomic Classification
Ye, S. H., Siddle, K. J., Park, D. J., & Sabeti, P. C. (2019) · Cell · doi:10.1016/j.cell.2019.07.010 · Cited by 593
Current challenges and best-practice protocols for microbiome analysis
Bharti, R., & Grimm, D. G. (2021) · Briefings in Bioinformatics · doi:10.1093/bib/bbz155 · Cited by 592
A review of methods and databases for metagenomic classification and assembly
Breitwieser, F. P., Lu, J., & Salzberg, S. L. (2019) · Briefings in Bioinformatics · doi:10.1093/bib/bbx120 · Cited by 566
Pan-cancer analyses reveal cancer-type-specific fungal ecologies and bacteriome interactions
Narunsky-Haziza, L., Sepich-Poore, G. D., Livyatan, I., Asraf, O., Martino, C., Nejman, D., Gavert, N., Stajich, J. E., Amit, G., González, A., et al. (2022) · Cell · doi:10.1016/j.cell.2022.09.005 · Cited by 538
Evaluating the Information Content of Shallow Shotgun Metagenomics
Hillmann, B., Al-Ghalith, G. A., Shields-Cutler, R. R., Zhu, Q., Gohl, D. M., Beckman, K. B., Knight, R., & Knights, D. (2018) · mSystems · doi:10.1128/msystems.00069-18 · Cited by 474
“These concerns can be alleviated to some extent using deep shotgun sequencing and metagenomic assembly (10), coabundance clustering (11), or proximity-based assembly (28), and de novo identification of strains from complex metagenomes remains an active area of research.”
BackgroundNovel soil bacteria possess diverse genes for secondary metabolite biosynthesis
Crits-Christoph, A., Diamond, S., Butterfield, C. N., Thomas, B. C., & Banfield, J. F. (2018) · Nature · doi:10.1038/s41586-018-0207-y · Cited by 435
Accurate and complete genomes from metagenomes
Chen, L.-X., Anantharaman, K., Shaiber, A., Eren, A. M., & Banfield, J. F. (2020) · Genome Research · doi:10.1101/gr.258640.119 · Cited by 401
Deep mitochondrial origin outside the sampled alphaproteobacteria
Martijn, J., Vosseberg, J., Guy, L., Offre, P., & Ettema, T. J. G. (2018) · Nature · doi:10.1038/s41586-018-0059-5 · Cited by 378
Biosynthetic potential of the global ocean microbiome
Paoli, L., Ruscheweyh, H.-J., Forneris, C. C., Hubrich, F., Kautsar, S., Bhushan, A., Lotti, A., Clayssen, Q., Salazar, G., Milanese, A., et al. (2022) · Nature · doi:10.1038/s41586-022-04862-3 · Cited by 384
Zhao, R., Yu, K., Zhang, J., Zhang, G., Huang, J., Ma, L., Deng, C., Li, X., & Li, B. (2020) · Water Research · doi:10.1016/j.watres.2020.116318 · Cited by 375
Pérez-Cobas, A. E., Gomez-Valero, L., & Buchrieser, C. (2020) · Microbial Genomics · doi:10.1099/mgen.0.000409 · Cited by 314
GroopM: an automated tool for the recovery of population genomes from related metagenomes
Imelfort, M., Parks, D., Woodcroft, B. J., Dennis, P., Hugenholtz, P., & Tyson, G. W. (2014) · PeerJ · doi:10.7717/peerj.603 · Cited by 317
The food-gut axis: lactic acid bacteria and their link to food, the gut microbiome and human health
De Filippis, F., Pasolli, E., & Ercolini, D. (2020) · FEMS Microbiology Reviews · doi:10.1093/femsre/fuaa015 · Cited by 303
GUNC: detection of chimerism and contamination in prokaryotic genomes
Orakov, A., Fullam, A., Coelho, L. P., Khedkar, S., Szklarczyk, D., Mende, D. R., Schmidt, T. S. B., & Bork, P. (2021) · Genome Biology · doi:10.1186/s13059-021-02393-0 · Cited by 299
Diagnostic potential and interactive dynamics of the colorectal cancer virome
Hannigan, G. D., Duhaime, M. B., Ruffin, M. T., Koumpouras, C. C., & Schloss, P. D. (2018) · mBio · doi:10.1128/mbio.02248-18 · Cited by 298
Campanaro, S., Treu, L., Kougias, P. G., De Francisci, D., Valle, G., & Angelidaki, I. (2016) · Biotechnology for Biofuels · doi:10.1186/s13068-016-0441-1 · Cited by 285
Xu, L., Dong, Z., Chiniquy, D., Pierroz, G., Deng, S., Gao, C., Diamond, S., Simmons, T., Wipf, H. M.-L., Caddell, D., et al. (2021) · Nature Communications · doi:10.1038/s41467-021-23553-7 · Cited by 282
Identifying biases and their potential solutions in human microbiome studies
Nearing, J. T., Comeau, A. M., & Langille, M. G. I. (2021) · Microbiome · doi:10.1186/s40168-021-01059-0 · Cited by 240
Genome-reconstruction for eukaryotes from complex natural microbial communities
West, P. T., Probst, A. J., Grigoriev, I. V., Thomas, B. C., & Banfield, J. F. (2018) · Genome Research · doi:10.1101/gr.228429.117 · Cited by 266
Microbial functional diversity: From concepts to applications
Escalas, A., Hale, L., Voordeckers, J. W., Yang, Y., Firestone, M. K., Alvarez‐Cohen, L., & Zhou, J. (2019) · Ecology and Evolution · doi:10.1002/ece3.5670 · Cited by 265
Neave, M. J., Michell, C. T., Apprill, A., & Voolstra, C. R. (2017) · Scientific Reports · doi:10.1038/srep40579 · Cited by 264
Vollmers, J., Wiegand, S., & Kaster, A.-K. (2017) · PLoS ONE · doi:10.1371/journal.pone.0169662 · Cited by 240
Kent, A. G., Vill, A. C., Shi, Q., Satlin, M. J., & Brito, I. L. (2020) · Nature Communications · doi:10.1038/s41467-020-18164-7 · Cited by 216
Drivers and determinants of strain dynamics following fecal microbiota transplantation
Schmidt, T. S. B., Li, S. S., Maistrenko, O. M., Akanni, W., Coelho, L. P., Dolai, S., Fullam, A., Glazek, A. M., Hercog, R., Herrema, H., et al. (2022) · Nature Medicine · doi:10.1038/s41591-022-01913-0 · Cited by 233
Brooks, B., Olm, M. R., Firek, B. A., Baker, R., Thomas, B. C., Morowitz, M. J., & Banfield, J. F. (2017) · Nature Communications · doi:10.1038/s41467-017-02018-w · Cited by 226
A Review of bioinformatics tools for bio-prospecting from metagenomic sequence data
Roumpeka, D. D., Wallace, R. J., Escalettes, F., Fotheringham, I., & Watson, M. (2017) · Frontiers in Genetics · doi:10.3389/fgene.2017.00023 · Cited by 199
“Thus, CONCOCT has been suggested for extracting biologically important information and could possibly contribute to recovery after infection.”
BackgroundMethodInfluentialBeresford-Jones, B. S., Forster, S. C., Stares, M. D., Notley, G., Viciani, E., Browne, H. P., Boehmler, D. J., Soderholm, A. T., Kumar, N., Vervier, K., et al. (2022) · Cell Host & Microbe · doi:10.1016/j.chom.2021.12.003 · Cited by 194
Delmont, T. O., Gaia, M., Hinsinger, D. D., Frémont, P., Vanni, C., Fernandez-Guerra, A., Eren, A. M., Kourlaiev, A., d'Agata, L., Clayssen, Q., et al. (2022) · Cell Genomics · doi:10.1016/j.xgen.2022.100123 · Cited by 173
A gut microbial signature for combination immune checkpoint blockade across cancer types
Gunjur, A., Shao, Y., Rozday, T., Klein, O., Mu, A., Haak, B. W., Markman, B., Kee, D., Carlino, M. S., Underhill, C., et al. (2024) · Nature Medicine · doi:10.1038/s41591-024-02823-z · Cited by 165
Svartström, O., Alneberg, J., Terrapon, N., Lombard, V., de Bruijn, I., Malmsten, J., Dalin, A.-M., EL Muller, E., Shah, P., Wilmes, P., et al. (2017) · The ISME Journal · doi:10.1038/ismej.2017.108 · Cited by 161
Self-citationMuñoz-Gómez, S. A., Susko, E., Williamson, K., Eme, L., Slamovits, C. H., Moreira, D., López-García, P., & Roger, A. J. (2022) · Nature Ecology & Evolution · doi:10.1038/s41559-021-01638-2 · Cited by 111
Metabolic network modeling of microbial communities
Biggs, M. B., Medlock, G. L., Kolling, G. L., & Papin, J. A. (2015) · WIREs Systems Biology and Medicine · doi:10.1002/wsbm.1308 · Cited by 124
Shotgun Metagenomics of a Water Kefir Fermentation Ecosystem Reveals a Novel Oenococcus Species
Verce, M., De Vuyst, L., & Weckx, S. (2019) · Frontiers in Microbiology · doi:10.3389/fmicb.2019.00479 · Cited by 121
Mirusviruses link herpesviruses to giant viruses
Gaïa, M., Meng, L., Pelletier, E., Forterre, P., Vanni, C., Fernandez-Guerra, A., Jaillon, O., Wincker, P., Ogata, H., Krupovic, M., et al. (2023) · Nature · doi:10.1038/s41586-023-05962-4 · Cited by 108
Metabolic independence drives gut microbial colonization and resilience in health and disease
Watson, A. R., Füssel, J., Veseli, I., DeLongchamp, J. Z., Silva, M., Trigodet, F., Lolans, K., Shaiber, A., Fogarty, E., Runde, J. M., et al. (2023) · Genome Biology · doi:10.1186/s13059-023-02924-x · Cited by 92
Self-citationTamburini, F. B., Maghini, D., Oduaran, O. H., Brewster, R., Hulley, M. R., Sahibdeen, V., Norris, S. A., Tollman, S., Kahn, K., Wagner, R. G., et al. (2022) · Nature Communications · doi:10.1038/s41467-021-27917-x · Cited by 88
Phelps, C. M., Willis, N. B., Duan, T., Lee, A. H., Zhang, Y., Rodriguez J, D. M., Pandey, S. P., Laughlin, C. R., Rosen, A. B. I., McPherson, A. C., et al. (2025) · Cell · doi:10.1016/j.cell.2025.06.018 · Cited by 91
Microbial hitchhikers harbouring antimicrobial-resistance genes in the riverine plastisphere
Zadjelovic, V., Wright, R. J., Borsetto, C., Quartey, J., Cairns, T. N., Langille, M. G. I., Wellington, E. M. H., & Christie-Oleza, J. A. (2023) · Microbiome · doi:10.1186/s40168-023-01662-3 · Cited by 87
The diversity and evolution of microbial dissimilatory phosphite oxidation
Ewens, S. D., Gomberg, A. F. S., Barnum, T. P., Borton, M. A., Carlson, H. K., Wrighton, K. C., & Coates, J. D. (2021) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2020024118 · Cited by 48
Gut microbiota in ALS: possible role in pathogenesis?
McCombe, P. A., Henderson, R. D., Lee, A., Lee, J. D., Woodruff, T. M., Restuadi, R., McRae, A., Wray, N. R., Ngo, S., & Steyn, F. J. (2019) · Expert Review of Neurotherapeutics · doi:10.1080/14737175.2019.1623026 · Cited by 46
Mycobacteriaceae Mineralizes Micropolyethylene in Riverine Ecosystems.
Sun, X., Chen, Z., Kong, T., Chen, Z., Dong, Y., Kolton, M., Cao, Z., Zhang, X., Zhang, H., Liu, G., et al. (2022) · Environmental Science & Technology · doi:10.1021/acs.est.2c05346 · Cited by 46
Alexander, H., Hu, S. K., Krinos, A. I., Pachiadaki, M., Tully, B. J., Neely, C. J., & Reiter, T. (2021) · doi:10.1101/2021.07.25.453713 · Cited by 67
Jeraldo, P., Hernandez, A., Nielsen, H. B., Chen, X., White, B. A., Goldenfeld, N., Nelson, H., Alhquist, D., Boardman, L., & Chia, N. (2016) · Frontiers in Microbiology · doi:10.3389/fmicb.2016.00783 · Cited by 38
Xie, F., Xu, L., Wang, Y., & Mao, S. (2021) · mSystems · doi:10.1128/msystems.00915-21 · Cited by 38
Kiu, R., Darby, E. M., Alcon-Giner, C., Acuna-Gonzalez, A., Camargo, A., Lamberte, L. E., Phillips, S., Sim, K., Shaw, A. G., Clarke, P., et al. (2025) · Nature communications · doi:10.1038/s41467-025-62584-2 · Cited by 36
Oxygen metabolism in descendants of the archaeal-eukaryotic ancestor
Appler, K. E., Lingford, J. P., Gong, X., Panagiotou, K., Leão, P., Langwig, M. V., Greening, C., Ettema, T. J. G., De Anda, V., & Baker, B. J. (2026) · Nature · doi:10.1038/s41586-026-10128-z · Cited by 36
Oxygen metabolism in descendants of the archaeal-eukaryotic ancestor
Appler, K. E., Lingford, J. P., Gong, X., Panagiotou, K., Leão, P., Langwig, M., Greening, C., Ettema, T. J. G., De Anda, V., & Baker, B. J. (2024) · doi:10.1101/2024.07.04.601786 · Cited by 36
Castro-Severyn, J., Pardo-Esté, C., Mendez, K. N., Fortt, J., Marquez, S., Molina, F., Castro-Nallar, E., Remonsellez, F., & Saavedra, C. P. (2021) · Microbiology Spectrum · doi:10.1128/spectrum.00444-21 · Cited by 36
Tomofuji, Y., Kishikawa, T., Maeda, Y., Ogawa, K., Otake-Kasamoto, Y., Kawabata, S., Nii, T., Okuno, T., Oguro-Igashira, E., Kinoshita, M., et al. (2022) · Cell Genomics · doi:10.1016/j.xgen.2022.100219 · Cited by 35
Pietrzak, B., Tomela, K., Olejnik-Schmidt, A., Galus, Ł., Mackiewicz, J., Kaczmarek, M., Mackiewicz, A., & Schmidt, M. (2022) · Cancers · doi:10.3390/cancers14215369 · Cited by 36
Nicotinamide Riboside-Conditioned Microbiota Deflects High-Fat Diet-Induced Weight Gain in Mice
Lozada-Fernández, V. V., deLeon, O., Kellogg, S. L., Saravia, F. L., Hadiono, M. A., Atkinson, S. N., Grobe, J. L., & Kirby, J. R. (2022) · mSystems · doi:10.1128/msystems.00230-21 · Cited by 23
Nitrate-driven anaerobic oxidation of ethane and butane by bacteria
Wu, M., Li, J., Lai, C.-Y., Leu, A. O., Sun, S., Gu, R., Erler, D. V., Liu, L., Li, L., Tyson, G. W., et al. (2024) · The ISME Journal · doi:10.1093/ismejo/wrad011 · Cited by 23
Reductive acetogenesis is a dominant process in the ruminant hindgut
Li, Q., Huo, J., Ni, G., Zhang, F., Zhang, S., Zhang, X., Wang, R., Jiao, J., Yu, Z., Pu, X., et al. (2025) · Microbiome · doi:10.1186/s40168-024-02018-1 · Cited by 22
Han, Y., Deng, Z., Peng, Y., Peng, J., Cao, L., Xu, Y., Yang, Y., Zhou, H., Zhang, C., Zhang, D., et al. (2025) · Microbiome · doi:10.1186/s40168-025-02147-1 · Cited by 21
Plastic biodegradation by sediment microbial populations under denitrifying conditions
Sun, X., Wang, S., Lin, Z., Chen, Z., Huang, W., Kong, T., Huang, D., Li, B., Zhang, H., & Sun, W. (2025) · Environmental Science & Technology · doi:10.1021/acs.est.4c12187 · Cited by 20
Genomic atlas of Bifidobacterium infantis and B. longum informs infant probiotic design
Shao, Y., Wang, S., Gichuki, B. M., Stares, M. D., Rozday, T. J., Kumar, N., Browne, H. P., Dawson, N. J. R., Njunge, J. M., Tigoi, C., et al. (2026) · Cell · doi:10.1016/j.cell.2026.01.007 · Cited by 17
Viruses of sulfur oxidizing phototrophs encode genes for pigment, carbon, and sulfur metabolisms
Hesketh-Best, P. J., Bosco-Santos, A., Garcia, S. L., O’Beirne, M. D., Werne, J. P., Gilhooly, W. P., & Silveira, C. B. (2023) · Communications Earth & Environment · doi:10.1038/s43247-023-00796-4 · Cited by 16
Arikawa, K., & Hosokawa, M. (2023) · Computational and Structural Biotechnology Journal · doi:10.1016/j.csbj.2023.09.010 · Cited by 13
Zhou, Y., Zheng, J., Wu, Y., Zhang, W., & Jin, J. (2020) · BMC Genomics · doi:10.1186/s12864-020-6597-x · Cited by 12
A multi-modal deep language model for contaminant removal from metagenome-assembled genomes
Zou, B., Wang, J., Ding, Y., Zhang, Z., Huang, Y., Fang, X., Cheung, K. C., See, S., & Zhang, L. (2024) · Nature Machine Intelligence · doi:10.1038/s42256-024-00908-5 · Cited by 9
Peng, J., Liu, X., Wang, J., Meng, N., Cai, R., Peng, Y., Han, Y., Liao, J., Li, C., Rubin-Blum, M., et al. (2025) · Microbiome · doi:10.1186/s40168-025-02280-x · Cited by 6
Metadata
- Authors
- Alneberg, J., Bjarnason, B. S., de Bruijn, I., Schirmer, M., Quick, J., Ijaz, U. Z., Lahti, L., Loman, N. J., Andersson, A. F., & Quince, C.
- Venue
- Nature Methods
- Published
- 2014-09-14
- Volume
- 11
- Issue
- 11
- Pages
- 1144-1146
- ISSN
- 1548-7091 (ISSN-L)
- 1548-7105
- OpenAlex
- W2103901746
- Cited by
- 2,800
- References
- 3
- FWCI
- 25.92
- Type
- journal article
- Language
- en
- Open access
- green
- Licence
- www.springer.com/tdm (tdm)
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.