The European nucleotide archive
Open accessAbstract
The European Nucleotide Archive (ENA; http://www.ebi.ac.uk/ena) is Europe's primary nucleotide-sequence repository. The ENA consists of three main databases: the Sequence Read Archive (SRA), the Trace Archive and EMBL-Bank. The objective of ENA is to support and promote the use of nucleotide sequencing as an experimental research platform by providing data submission, archive, search and download services. In this article, we outline these services and describe major changes and improvements introduced during 2010. These include extended EMBL-Bank and SRA-data submission services, extended ENA Browser functionality, support for submitting data to the European Genome-phenome Archive (EGA) through SRA, and the launch of a new sequence similarity search service.
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Tools such as DIGIT and Abysis source their data from the European Nucleotide Archive (ENA) and the National Center for Biotechnology Information (NCBI); their sequence volumes are of the order of 105 and contain multiple artificially engineered sequences.
“Tools such as DIGIT and Abysis source their data from the European Nucleotide Archive (ENA) [60] and the National Center for Biotechnology Information (NCBI) [61]; their sequence volumes are of the order of 105 and contain multiple artificially engineered sequences.”
From Computational approaches to therapeutic antibody design: established methods and emerging trends (2020) · cites this paper as [60]
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The Sequence Alignment/Map format and SAMtools
Li, H., Handsaker, B., Wysoker, A., Fennell, T., Ruan, J., Homer, N., Marth, G., Abecasis, G., Durbin, R., & 1000 Genome Project Data Processing Subgroup (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp352 · Cited by 62,041 · see citing works
Velvet: Algorithms for de novo short read assembly using de Bruijn graphsPreprint
Zerbino, D. R., & Birney, E. (2008) · Genome Research · doi:10.1101/gr.074492.107 · Cited by 9,387 · see citing works
Automated generation of heuristics for biological sequence comparison
Slater, G., & Birney, E. (2005) · BMC Bioinformatics · doi:10.1186/1471-2105-6-31 · Cited by 2,902 · see citing works
The International Nucleotide Sequence Database Collaboration
Karsch‐Mizrachi, I., Nakamura, Y., & Cochrane, G. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr1006 · Cited by 717 · see citing works
Benson, D. A., Karsch‐Mizrachi, I., Lipman, D. J., Ostell, J., & Sayers, E. W. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp1024 · Cited by 348 · see citing works
Krause, J., Unger, T., Noçon, A., Malaspinas, A., Kolokotronis, S., Stiller, M., Soibelzon, L. H., Spriggs, H. F., Dear, P. H., Briggs, A. W., et al. (2008) · BMC Evolutionary Biology · doi:10.1186/1471-2148-8-220 · Cited by 285 · see citing works
The International Nucleotide Sequence Database Collaboration
Cochrane, G., Karsch‐Mizrachi, I., & Nakamura, Y. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq1150 · Cited by 113 · see citing works
DDBJ launches a new archive database with analytical tools for next-generation sequence data
Kaminuma, E., Mashima, J., Kodama, Y., Gojobori, T., Ogasawara, O., Okubo, K., Takagi, T., & Nakamura, Y. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp847 · Cited by 99 · see citing works
Improvements to services at the European Nucleotide Archive
Leinonen, R., Akhtar, R. A., Birney, E., Bonfield, J., Bower, L., Corbett, M., Cheng, Y., Demiralp, F., Faruque, N., Goodgame, N., et al. (2009) · Nucleic Acids Research · doi:10.1093/nar/gkp998 · Cited by 66 · see citing works
Fast and efficient searching of biological data resources--using EB-eye
Valentin, F., Squizzato, S., Goujon, M., McWilliam, H., Paern, J., & López, R. (2010) · Briefings in Bioinformatics · doi:10.1093/bib/bbp065 · Cited by 37 · see citing works
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Benson, D. A., Cavanaugh, M., Clark, K., Karsch-Mizrachi, I., Lipman, D. J., Ostell, J., & Sayers, E. W. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1195 · Cited by 3,261 · see citing works
Beghini, F., McIver, L. J., Blanco-Míguez, A., Dubois, L., Asnicar, F., Maharjan, S., Mailyan, A., Manghi, P., Scholz, M., Thomas, A. M., et al. (2021) · eLife · doi:10.7554/elife.65088 · Cited by 2,303 · see citing works
Improvements to PATRIC, the all-bacterial Bioinformatics Database and Analysis Resource Center
Wattam, A. R., Davis, J. J., Assaf, R., Boisvert, S., Brettin, T. S., Bun, C., Conrad, N. R., Dietrich, E. M., Disz, T. L., Gabbard, J. L., et al. (2016) · Nucleic Acids Research · doi:10.1093/nar/gkw1017 · Cited by 1,635 · see citing works
Landscape of Microsatellite Instability Across 39 Cancer Types
Bonneville, R., Krook, M. A., Kautto, E. A., Miya, J., Wing, M. R., Chen, H., Reeser, J. W., Yu, L., & Roychowdhury, S. (2017) · JCO Precision Oncology · doi:10.1200/po.17.00073 · Cited by 1,474 · see citing works
Gide, T. N., Quek, C., Menzies, A. M., Tasker, A. T., Shang, P., Holst, J., Madore, J., Lim, S. Y., Velickovic, R., Wongchenko, M., et al. (2019) · Cancer Cell · doi:10.1016/j.ccell.2019.01.003 · Cited by 1,047 · see citing works
Pagani, I., Liolios, K., Jansson, J., Chen, I.-M. A., Smirnova, T., Nosrat, B., Markowitz, V. M., & Kyrpides, N. C. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr1100 · Cited by 1,061 · see citing works
25 years of serving the community with ribosomal RNA gene reference databases and tools
Glöckner, F. O., Yilmaz, P., Quast, C., Gerken, J., Beccati, A., Ciuprina, A., Bruns, G., Yarza, P., Peplies, J., Westram, R., et al. (2017) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2017.06.1198 · Cited by 951 · see citing works
Using machine learning approaches for multi-omics data analysis: A review
Reel, P. S., Reel, S., Pearson, E., Trucco, E., & Jefferson, E. (2021) · Biotechnology Advances · doi:10.1016/j.biotechadv.2021.107739 · Cited by 903 · see citing works
RobiNA: a user-friendly, integrated software solution for RNA-Seq-based transcriptomics
Lohse, M., Bolger, A., Nagel, A., Fernie, A. R., Lunn, J. E., Stitt, M., & Usadel, B. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks540 · Cited by 778 · see citing works
Bias, robustness and scalability in single-cell differential expression analysis
Soneson, C., & Robinson, M. D. (2018) · Nature Methods · doi:10.1038/nmeth.4612 · Cited by 770 · see citing works
OptiType: precision HLA typing from next-generation sequencing data
Szolek, A., Schubert, B., Mohr, C., Sturm, M., Feldhahn, M., & Kohlbacher, O. (2014) · Bioinformatics · doi:10.1093/bioinformatics/btu548 · Cited by 762 · see citing works
Cistrome: an integrative platform for transcriptional regulation studies
Liu, T., Ortiz, J. A., Taing, L., Meyer, C. A., Lee, B. T. K., Zhang, Y., Shin, H., Wong, S. S., Ma, J., Lei, Y., et al. (2011) · Genome biology · doi:10.1186/gb-2011-12-8-r83 · Cited by 705 · see citing works
The International Nucleotide Sequence Database Collaboration
Karsch‐Mizrachi, I., Nakamura, Y., & Cochrane, G. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr1006 · Cited by 717 · see citing works
Massive expansion of human gut bacteriophage diversity
Camarillo-Guerrero, L. F., Almeida, A., Rangel-Pineros, G., Finn, R. D., & Lawley, T. D. (2021) · Cell · doi:10.1016/j.cell.2021.01.029 · Cited by 594 · see citing works
Update on the proposed minimal standards for the use of genome data for the taxonomy of prokaryotes
Riesco, R., & Trujillo, M. E. (2024) · INTERNATIONAL JOURNAL OF SYSTEMATIC AND EVOLUTIONARY MICROBIOLOGY · doi:10.1099/ijsem.0.006300 · Cited by 596 · see citing works
Benson, D. A., Karsch‐Mizrachi, I., Clark, K., Lipman, D. J., Ostell, J., & Sayers, E. W. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr1202 · Cited by 589 · see citing works
Scheinin, I., Sie, D., Bengtsson, H. L., van de Wiel, M. A., Olshen, A. B., van Thuijl, H. F., Essen, H. F. H. V., Eijk, P. P., Rustenburg, F., Meijer, G. A., et al. (2014) · Genome Research · doi:10.1101/gr.175141.114 · Cited by 491 · see citing works
Oulas, A., Pavloudi, C., Polymenakou, P., Pavlopoulos, G. A., Papanikolaou, N., Kotoulas, G., Arvanitidis, C., & Iliopoulos, L. (2015) · Bioinformatics and Biology Insights · doi:10.4137/bbi.s12462 · Cited by 423 · see citing works
The Ontology for Biomedical Investigations
Bandrowski, A. E., Brinkman, R. R., Brochhausen, M., Brush, M., Bug, B., Chibucos, M. C., Clancy, K., Courtot, M., Derom, D., Dumontier, M., et al. (2016) · PLoS ONE · doi:10.1371/journal.pone.0154556 · Cited by 387 · see citing works
A brief history of bioinformatics
Gauthier, J., Vincent, A. T., Charette, S. J., & Derôme, N. (2018) · Briefings in Bioinformatics · doi:10.1093/bib/bby063 · Cited by 388 · see citing works
The real cost of sequencing: scaling computation to keep pace with data generation
Muir, P., Li, S., Lou, S., Wang, D., Spakowicz, D. J., Salichos, L., Zhang, J., Weinstock, G. M., Isaacs, F. J., Rozowsky, J. S., et al. (2016) · Genome biology · doi:10.1186/s13059-016-0917-0 · Cited by 369 · see citing works
Reddy, T. B. K., Thomas, A. D., Stamatis, D., Bertsch, J., Isbandi, M., Jansson, J., Mallajosyula, J. K., Pagani, I., Lobos, E. A., & Kyrpides, N. C. (2014) · Nucleic Acids Research · doi:10.1093/nar/gku950 · Cited by 334 · see citing works
Transcriptome analysis of human tissues and cell lines reveals one dominant transcript per gene
Gonzàlez-Porta, M., Frankish, A., Rung, J., Harrow, J., & Brazma, A. (2013) · Genome Biology · doi:10.1186/gb-2013-14-7-r70 · Cited by 266 · see citing works
Protein interaction networks revealed by proteome coevolution
Cong, Q., Anishchenko, I., Ovchinnikov, S., & Baker, D. (2019) · Science · doi:10.1126/science.aaw6718 · Cited by 241 · see citing works
Ancient plant DNA in lake sediments
Parducci, L., Bennett, K. D., Ficetola, G. F., Alsos, I. G., Suyama, Y., Wood, J. R., & Pedersen, M. W. (2017) · New Phytologist · doi:10.1111/nph.14470 · Cited by 276 · see citing works
de Klein, N., Tsai, E. A., Vochteloo, M., Baird, D., Huang, Y., Chen, C.-Y., van Dam, S., Oelen, R., Deelen, P., Bakker, O. B., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01300-6 · Cited by 272 · see citing works
Comparison of solution-based exome capture methods for next generation sequencing
Sulonen, A.-M., Ellonen, P., Almusa, H., Lepistö, M., Eldfors, S., Hannula, S., Miettinen, T., Tyynismaa, H., Salo, P. P., Heckman, C. A., et al. (2011) · Genome biology · doi:10.1186/gb-2011-12-9-r94 · Cited by 265 · see citing works
Mitotic Transcription and Waves of Gene Reactivation During Mitotic Exit
Palozola, K. C., Donahue, G., Liu, H., Grant, G., Becker, J., Coté, A., Yu, H.-T., Raj, A., & Zaret, K. (2017) · Science · doi:10.1126/science.aal4671 · Cited by 245 · see citing works
Disbiome database: linking the microbiome to disease
Janssens, Y., Nielandt, J., Bronselaer, A., Debunne, N., Verbeke, F., Wynendaele, E., Immerseel, F. V., Vandewynckel, Y., Tré, G. D., & Spiegeleer, B. D. (2018) · BMC Microbiology · doi:10.1186/s12866-018-1197-5 · Cited by 250 · see citing works
Kovaltsuk, A., Leem, J., Kelm, S., Snowden, J., Deane, C. M., & Krawczyk, K. (2018) · The Journal of Immunology · doi:10.4049/jimmunol.1800708 · Cited by 247 · see citing works
The switches.ELM Resource: A Compendium of Conditional Regulatory Interaction Interfaces
Roey, K. V., Dinkel, H., Weatheritt, R. J., Gibson, T. J., & Davey, N. E. (2013) · Science Signaling · doi:10.1126/scisignal.2003345 · Cited by 247 · see citing works
Genenames.org: the HGNC resources in 2013
Gray, K. A., Daugherty, L. C., Gordon, S. M., Seal, R. L., Wright, M. W., & Bruford, E. A. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1066 · Cited by 240 · see citing works
Architectures of Lipid Transport Systems for the Bacterial Outer Membrane
Ekiert, D. C., Bhabha, G., Isom, G. L., Greenan, G. A., Ovchinnikov, S., Henderson, I. R., Cox, J. S., & Vale, R. D. (2017) · Cell · doi:10.1016/j.cell.2017.03.019 · Cited by 221 · see citing works
GeneDB--an annotation database for pathogens
Logan-Klumpler, F., Silva, N. H. D., Böehme, U., Rogers, M. B., Velarde, G., McQuillan, J. A., Carver, T., Aslett, M. A., Olsen, C., Subramanian, S., et al. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr1032 · Cited by 228 · see citing works
Computational approaches to therapeutic antibody design: established methods and emerging trends
Norman, R. A., Ambrosetti, F., Bonvin, A. M. J. J., Colwell, L. J., Kelm, S., Kumar, S., & Krawczyk, K. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbz095 · Cited by 219 · see citing works
“Tools such as DIGIT and Abysis source their data from the European Nucleotide Archive (ENA) [60] and the National Center for Biotechnology Information (NCBI) [61]; their sequence volumes are of the order of 105 and contain multiple artificially engineered sequences.”
MethodDesigning a transcriptome next‐generation sequencing project for a nonmodel plant species1
Strickler, S. R., Bombarely, A., & Mueller, L. A. (2012) · American Journal of Botany · doi:10.3732/ajb.1100292 · Cited by 222 · see citing works
CopywriteR: DNA copy number detection from off-target sequence data
Kuilman, T., Velds, A., Kemper, K., Ranzani, M., Bombardelli, L., Hoogstraat, M., Nevedomskaya, E., Xu, G., de Ruiter, J., Lolkema, M. P., et al. (2015) · Genome biology · doi:10.1186/s13059-015-0617-1 · Cited by 214 · see citing works
HBVdb: a knowledge database for Hepatitis B Virus
Hayer, J., Jadeau, F., Deléage, G., Kay, A., Zoulim, F., & Combet, C. (2012) · Nucleic Acids Research · doi:10.1093/nar/gks1022 · Cited by 212 · see citing works
Chromatin accessibility profiling methods
Minnoye, L., Marinov, G. K., Krausgruber, T., Pan, L., Marand, A. P., Secchia, S., Greenleaf, W. J., Furlong, E. E. M., Zhao, K., Schmitz, R. J., et al. (2021) · Nature Reviews Methods Primers · doi:10.1038/s43586-020-00008-9 · Cited by 206 · see citing works
Lentendu, G., Wubet, T., Chatzinotas, A., Wilhelm, C., Buscot, F., & Schlegel, M. (2014) · Molecular Ecology · doi:10.1111/mec.12819 · Cited by 193 · see citing works
The International Human Epigenome Consortium Data Portal
Bujold, D., Morais, D. A. D. L., Gauthier, C., Côté, C., Caron, M., Kwan, T., Chen, K. C., Laperle, J., Nordell-Markovits, A., Pastinen, T., et al. (2016) · Cell Systems · doi:10.1016/j.cels.2016.10.019 · Cited by 186 · see citing works
Temporal and technical variability of human gut metagenomes
Voigt, A. Y., Costea, P. I., Kultima, J. R., Li, S. S., Zeller, G., Sunagawa, S., & Bork, P. (2015) · Genome biology · doi:10.1186/s13059-015-0639-8 · Cited by 177 · see citing works
Lightbody, G., Haberland, V., Browne, F., Taggart, L., Zheng, H., Parkes, E., & Blayney, J. K. (2019) · Briefings in Bioinformatics · doi:10.1093/bib/bby051 · Cited by 173 · see citing works
One Stop Shop for Everything Dictyostelium: dictyBase and the Dicty Stock Center in 2012
Fey, P., Dodson, R. J., Basu, S., & Chisholm, R. L. (2013) · Methods in molecular biology · doi:10.1007/978-1-62703-302-2_4 · Cited by 166 · see citing works
Krishna, A., Biryukov, M., Trefois, C., Antony, P. M. A., Hussong, R., Lin, J., Heinäniemi, M., Glusman, G., Köglsberger, S., Boyd, O., et al. (2014) · BMC Genomics · doi:10.1186/1471-2164-15-1154 · Cited by 165 · see citing works
Kapushesky, M., Adamusiak, T., Burdett, T., Culhane, A. C., Farne, A., Filippov, A., Holloway, E., Клебанов, А. А., Kryvych, N., Kurbatova, N., et al. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr913 · Cited by 164 · see citing works
Gene regulatory network inference resources: A practical overview
Mercatelli, D., Scalambra, L., Triboli, L., Ray, F., & Giorgi, F. M. (2019) · Biochimica et Biophysica Acta (BBA) - Gene Regulatory Mechanisms · doi:10.1016/j.bbagrm.2019.194430 · Cited by 157 · see citing works
Deelen, P., van Dam, S., Herkert, J. C., Karjalainen, J. M., Brugge, H., Abbott, K. M., van Diemen, C. C., van der Zwaag, P. A., Gerkes, E. H., Zonneveld-Huijssoon, E., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-10649-4 · Cited by 138 · see citing works
A Guide to Carrying Out a Phylogenomic Target Sequence Capture Project
Andermann, T., Jiménez, M. F. T., Matos‐Maraví, P. F., Batista, R., Blanco‐Pastor, J. L., Gustafsson, A. L. S., Kistler, L., Liberal, I. M., Oxelman, B., Bacon, C. D., et al. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2019.01407 · Cited by 139 · see citing works
Beginner’s guide to comparative bacterial genome analysis using next-generation sequence data
Edwards, D., & Holt, K. E. (2013) · Microbial Informatics and Experimentation · doi:10.1186/2042-5783-3-2 · Cited by 139 · see citing works
ESSENTIALS: Software for Rapid Analysis of High Throughput Transposon Insertion Sequencing Data
Zomer, A., Burghout, P., Bootsma, H. J., Hermans, P. W. M., & van Hijum, S. A. F. T. (2012) · PLoS ONE · doi:10.1371/journal.pone.0043012 · Cited by 138 · see citing works
Hellinger, R., Sigurdsson, A., Wu, W., Romanova, E. V., Li, L., Sweedler, J. V., Süßmuth, R. D., & Gruber, C. W. (2023) · Nature Reviews Methods Primers · doi:10.1038/s43586-023-00205-2 · Cited by 134 · see citing works
Reference databases for taxonomic assignment in metagenomics
Santamaría, M., Fosso, B., Consiglio, A., Caro, G. D., Grillo, G., Licciulli, F., Liuni, S., Marzano, M., Alonso-Alemany, D., Valiente, G., et al. (2012) · Briefings in Bioinformatics · doi:10.1093/bib/bbs036 · Cited by 130 · see citing works
WheatExp: an RNA-seq expression database for polyploid wheat
Pearce, S. P., Vasquez-Gross, H. A., Herin, S. Y., Hane, D. L., Wang, Y., Gu, Y., & Dubcovsky, J. (2015) · BMC Plant Biology · doi:10.1186/s12870-015-0692-1 · Cited by 130 · see citing works
PATRIC as a unique resource for studying antimicrobial resistance
Antonopoulos, D. A., Assaf, R., Aziz, R. K., Brettin, T. S., Bun, C., Conrad, N. R., Davis, J. J., Dietrich, E. M., Disz, T. L., Gerdes, S., et al. (2017) · Briefings in Bioinformatics · doi:10.1093/bib/bbx083 · Cited by 130 · see citing works
Gene co-expression network connectivity is an important determinant of selective constraint
Mähler, N., Wang, J., Terebieniec, B. K., Ingvarsson, P., Street, N., & Hvidsten, T. (2016) · bioRxiv · doi:10.1371/journal.pgen.1006402 · Cited by 124 · see citing works
Ten steps to get started in Genome Assembly and Annotation
Angel, V. D. D., Hjerde, E., Sterck, L., Capella-Gutiérrez, S., Notredame, C., Pettersson, O. V., Amselem, J., Bouri, L., Bocs, S., Klopp, C., et al. (2018) · F1000Research · doi:10.12688/f1000research.13598.1 · Cited by 123 · see citing works
Nilsson, R. H., Tedersoo, L., Lindahl, B. D., Kjøller, R., Carlsen, T., Quince, C., Abarenkov, K., Pennanen, T., Stenlid, J., Bruns, T. D., et al. (2011) · New Phytologist · doi:10.1111/j.1469-8137.2011.03755.x · Cited by 120 · see citing works
Biological Databases for Human Research
Zou, D., Ma, L., Yu, J. M., & Zhang, Z. (2015) · Genomics Proteomics & Bioinformatics · doi:10.1016/j.gpb.2015.01.006 · Cited by 118 · see citing works
The diversity and abundance of fungi and bacteria on the healthy and dandruff affected human scalp
Grimshaw, S. G., Smith, A. M., Arnold, D. S., Xu, E., Hoptroff, M., & Murphy, B. (2019) · PLoS ONE · doi:10.1371/journal.pone.0225796 · Cited by 115 · see citing works
The International Nucleotide Sequence Database Collaboration
Cochrane, G., Karsch‐Mizrachi, I., & Nakamura, Y. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq1150 · Cited by 113 · see citing works
Data analysis: Create a cloud commons
Stein, L. D., Knoppers, B. M., Campbell, P. J., Getz, G. A., & Korbel, J. O. (2015) · Nature · doi:10.1038/523149a · Cited by 110 · see citing works
Data integration in biological research: an overview
Lapatas, V., Stefanidakis, M., Jiménez, R. C., Via, A., & Schneider, M. V. (2015) · Journal of Biological Research - Thessaloniki · doi:10.1186/s40709-015-0032-5 · Cited by 104 · see citing works
A gene prioritization method based on a swine multi-omics knowledgebase and a deep learning model
Fu, Y., Xu, J., Tang, Z., Wang, L., Yin, D., Fan, Y., Zhang, D., Deng, F., Zhang, Y., Zhang, H., et al. (2020) · Communications Biology · doi:10.1038/s42003-020-01233-4 · Cited by 103 · see citing works
A resource of variant effect predictions of single nucleotide variants in model organisms
Wagih, O., Busby, B. P., Galardini, M., Memon, D., Typas, A., & Beltrão, P. (2018) · Molecular Systems Biology · doi:10.15252/msb.20188430 · Cited by 94 · see citing works
DNA Metabarcoding for the Characterization of Terrestrial Microbiota—Pitfalls and Solutions
Francioli, D., Lentendu, G., Lewin, S. A., & Kolb, S. (2021) · Microorganisms · doi:10.3390/microorganisms9020361 · Cited by 94 · see citing works
Benchmarking bioinformatic tools for fast and accurate eDNA metabarcoding species identification
Mathon, L., Valentini, A., Guérin, P., Normandeau, É., Noël, C., Lionnet, C., Boulanger, E., Thuiller, W., Bernatchez, L., Mouillot, D., et al. (2021) · Molecular Ecology Resources · doi:10.1111/1755-0998.13430 · Cited by 93 · see citing works
Ederveen, T. H. A., Ferwerda, G., Ahout, I. M. L., Vissers, M., de Groot, R., Boekhorst, J., Timmerman, H. M., Huynen, M. A., van Hijum, S. A. F. T., & de Jonge, M. I. (2018) · Microbiome · doi:10.1186/s40168-017-0395-y · Cited by 93 · see citing works
The 2011 Nucleic Acids Research Database Issue and the online Molecular Biology Database Collection
Galperin, M. Y., & Cochrane, G. (2010) · Nucleic Acids Research · doi:10.1093/nar/gkq1243 · Cited by 91 · see citing works
Use of Bioinformatics Tools in Different Spheres of Life Sciences
Mehmood, M. A. (2014) · Journal of Data Mining in Genomics & Proteomics · doi:10.4172/2153-0602.1000158 · Cited by 90 · see citing works
Derocles, S. A. P., Bohan, D. A., Dumbrell, A. J., Kitson, J. J. N., Massol, F., Pauvert, C., Plantegenest, M., Vacher, C., & Evans, D. M. (2018) · Advances in ecological research/Advances in Ecological Research · doi:10.1016/bs.aecr.2017.12.001 · Cited by 92 · see citing works
Experimental temperatures shape host microbiome diversity and composition
Li, J., Bates, K. A., Hoang, K. L., Hector, T. E., Knowles, S. C. L., & King, K. C. (2022) · Global Change Biology · doi:10.1111/gcb.16429 · Cited by 96 · see citing works
Chinese hamster genome database: An online resource for the CHO community at www.CHOgenome.org
Hammond, S., Kaplarevic, M., Borth, N., Betenbaugh, M. J., & Lee, K. H. (2011) · Biotechnology and Bioengineering · doi:10.1002/bit.24374 · Cited by 87 · see citing works
Sheflin, A. M., Borresen, E. C., Wdowik, M. J., Rao, S., Brown, R. J., Heuberger, A. L., Broeckling, C. D., Weir, T. L., & Ryan, E. P. (2015) · Nutrients · doi:10.3390/nu7021282 · Cited by 87 · see citing works
Boulanger, E., Loiseau, N., Valentini, A., Arnal, V., Boissery, P., Déjean, T., Déter, J., Guellati, N., Holon, F., Juhel, J., et al. (2021) · Proceedings of the Royal Society B Biological Sciences · doi:10.1098/rspb.2021.0112 · Cited by 81 · see citing works
Maleki‐Ravasan, N., Oshaghi, M. A., Afshar, D., Arandian, M. H., Hajikhani, S., Akhavan, A. A., Yakhchali, B., Shirazi, M. H., Rassi, Y., Jafari, R., et al. (2015) · Parasites & Vectors · doi:10.1186/s13071-014-0517-3 · Cited by 80 · see citing works
Beckert, P., Sánchez-Padilla, E., Merker, M., Dreyer, V., Kohl, T. A., Utpatel, C., Köser, C. U., Barilar, I., Ismail, N. A., Omar, S. V., et al. (2020) · Genome Medicine · doi:10.1186/s13073-020-00793-8 · Cited by 79 · see citing works
Vision, challenges and opportunities for a Plant Cell Atlas
Ahmed, J., Alaba, O., Ameen, G., Arora, V., Arteaga-Vazquez, M. A., Arun, A., Bailey-Serres, J. N., Bartley, L., Bassel, G. W., Bergmann, D. C., et al. (2021) · eLife · doi:10.7554/elife.66877 · Cited by 76 · see citing works
Triticeae Resources in Ensembl Plants
Bolser, D. M., Kerhornou, A., Walts, B., & Kersey, P. J. (2014) · Plant and Cell Physiology · doi:10.1093/pcp/pcu183 · Cited by 78 · see citing works
Zerbino, D., Johnson, N., Juetteman, T., Sheppard, D., Wilder, S. P., Lavidas, I., Nuhn, M., Perry, E., Raffaillac-Desfosses, Q., Sobral, D., et al. (2016) · Database J. Biol. Databases Curation · doi:10.1093/database/bav119 · Cited by 65 · see citing works
VIDHOP, viral host prediction with deep learning
Mock, F., Viehweger, A., Barth, E., & Marz, M. (2020) · Bioinformatics · doi:10.1093/bioinformatics/btaa705 · Cited by 74 · see citing works
READv2: advanced and user-friendly detection of biological relatedness in archaeogenomics
Alaçamlı, E., Naidoo, T., Güler, M. N., Sağlıcan, E., Aktürk, Ş., Mapelli, I., Vural, K. B., Somel, M., Malmström, H., & Günther, T. (2024) · Genome biology · doi:10.1186/s13059-024-03350-3 · Cited by 74 · see citing works
FORK-seq: replication landscape of the Saccharomyces cerevisiae genome by nanopore sequencing
Hennion, M., Arbona, J., Lacroix, L., Cruaud, C., Theulot, B., Tallec, B. L., Proux, F., Wu, X., Novikova, E., Engelen, S., et al. (2020) · Genome biology · doi:10.1186/s13059-020-02013-3 · Cited by 73 · see citing works
Nagasaki, H., Mochizuki, T., Kodama, Y., Saruhashi, S., Morizaki, S., Sugawara, H., Ohyanagi, H., Kurata, N., Okubo, K., Takagi, T., et al. (2013) · DNA Research · doi:10.1093/dnares/dst017 · Cited by 73 · see citing works
Phytotoxin production in Aspergillus terreus is regulated by independent environmental signals
Gressler, M., Meyer, F., Heine, D., Hortschansky, P., Hertweck, C., & Brock, M. (2015) · eLife · doi:10.7554/elife.07861 · Cited by 71 · see citing works
The microbiome in rheumatology: Where are we and where should we go?
Manasson, J., Blank, R. B., & Scher, J. U. (2020) · Annals of the Rheumatic Diseases · doi:10.1136/annrheumdis-2019-216631 · Cited by 71 · see citing works
RNAcentral: A vision for an international database of RNA sequences
Bateman, A. G., Agrawal, S., Birney, E., Bruford, E. A., Bujnicki, J. M., Cochrane, G., Cole, J. R., Dinger, M. E., Enright, A. J., Gardner, P. P., et al. (2011) · RNA · doi:10.1261/rna.2750811 · Cited by 73 · see citing works
High GC content causes orphan proteins to be intrinsically disordered
Basile, W., Sachenkova, O., Light, S., & Elofsson, A. (2017) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1005375 · Cited by 72 · see citing works
Brown, N., Cambruzzi, J., Cox, P. J., Davies, M., Dunbar, J., Plumbley, D., Sellwood, M. A., Sim, A., Williams-Jones, B. I., Zwierzyna, M., et al. (2018) · Progress in medicinal chemistry · doi:10.1016/bs.pmch.2017.12.003 · Cited by 71 · see citing works
Chermprapai, S., Ederveen, T. H. A., Broere, F., Broens, E. M., Schlotter, Y. M., van Schalkwijk, S., Boekhorst, J., van Hijum, S. A. F. T., & Rutten, V. P. M. G. (2018) · Veterinary Microbiology · doi:10.1016/j.vetmic.2018.12.022 · Cited by 72 · see citing works
Gommers, L. M. M., Ederveen, T. H. A., van der Wijst, J., Bos, C., Kortman, G. A. M., Boekhorst, J., Bindels, R. J. M., de Baaij, J. H. F., & Hoenderop, J. G. J. (2019) · The FASEB Journal · doi:10.1096/fj.201900839r · Cited by 70 · see citing works
The BioSample Database (BioSD) at the European Bioinformatics Institute
Gostev, M., Faulconbridge, A., Brandizi, M., Fernandez-Banet, J., Sarkans, U., Brāzma, A., & Parkinson, H. (2011) · Nucleic Acids Research · doi:10.1093/nar/gkr937 · Cited by 70 · see citing works
DNA traces the origin of honey by identifying plants, bacteria and fungi
Wirta, H., Abrego, N., Miller, K. E., Roslin, T. V., & Vesterinen, E. J. (2021) · Scientific Reports · doi:10.1038/s41598-021-84174-0 · Cited by 69 · see citing works
Multi-study inference of regulatory networks for more accurate models of gene regulation
Castro, D. M., Veaux, N. D., Miraldi, E. R., & Bonneau, R. (2019) · PLoS Computational Biology · doi:10.1371/journal.pcbi.1006591 · Cited by 69 · see citing works
Applications of deep learning in understanding gene regulation
Li, Z., Gao, E., Zhou, J., Han, W., Xu, X., & Gao, X. (2023) · Cell Reports Methods · doi:10.1016/j.crmeth.2022.100384 · Cited by 68 · see citing works
Solving the Problem: Genome Annotation Standards before the Data Deluge
Klimke, W. A., O’Donovan, C., White, O. R., Brister, J. R., Clark, K., Fedorov, B., Karsch‐Mizrachi, I., Pruitt, K. D., & Tatusova, T. A. (2011) · Standards in Genomic Sciences · doi:10.4056/sigs.2084864 · Cited by 67 · see citing works
Daptomycin Resistance in Clinical MRSA Strains Is Associated with a High Biological Fitness Cost
Roch, M., Gagetti, P. S., Davis, J. J., Ceriana, P., Errecalde, L., Corso, A. C., & Rosato, A. E. (2017) · Frontiers in Microbiology · doi:10.3389/fmicb.2017.02303 · Cited by 67 · see citing works
A vast evolutionarily transient translatome contributes to phenotype and fitness
Wacholder, A. C., Parikh, S. B., Coelho, N. C., Acar, O., Houghton, C. J., Chou, L., & Carvunis, A. (2023) · Cell Systems · doi:10.1016/j.cels.2023.04.002 · Cited by 66 · see citing works
Voigt, O., Adamski, M., Sluzek, K., & Adamska, M. (2014) · BMC Evolutionary Biology · doi:10.1186/s12862-014-0230-z · Cited by 63 · see citing works
Consensus Transcriptional Landscape of Human End‐Stage Heart Failure
Flores, R. O. R., Lanzer, J. D., Holland, C. H., Leuschner, F., Most, P., Schultz, J., Levinson, R. T., & Sáez-Rodríguez, J. (2021) · Journal of the American Heart Association · doi:10.1161/jaha.120.019667 · Cited by 65 · see citing works
- Authors
- Leinonen, R., Akhtar, R., Birney, E., Bower, L., Cerdeno-Tarraga, A., Cheng, Y., Cleland, I., Faruque, N., Goodgame, N., Gibson, R., Hoad, G., Jang, M., Pakseresht, N., Plaister, S., Radhakrishnan, R., Reddy, K., Sobhany, S., Ten Hoopen, P., Vaughan, R., Zalunin, V., & Cochrane, G.
- Affiliations
- European Bioinformatics Institute (GB)
- Corresponding author
- Leinonen, R.
- ORCID
- Venue
- Nucleic Acids Research
- Publisher
- Oxford University Press (OUP)
- Published
- 2010-10-23
- Volume
- 39
- Issue
- Database
- Pages
- D28-D31
- ISSN
- 0305-1048 (ISSN-L)
- 1362-4962
- PMC
- PMC3013801
- OpenAlex
- W2120358246
- Cited by
- 690
- References
- 10
- Citations by year
- 2026: 37 · 2025: 49 · 2024: 74 · 2023: 52 · 2022: 44 · 2021: 64 · 2020: 37 · 2019: 42 · 2018: 41 · 2017: 47 · 2016: 39 · 2015: 48 · 2014: 33 · 2013: 31 · 2012: 23
- FWCI
- 10.60
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- Nucleic Acids Research (publishedVersion, cc-by-nc)
- PubMed Central (publishedVersion, cc-by-nc)
- PubMed (publishedVersion)
- Funders
- Wellcome Trust (085532)
- European Molecular Biology Laboratory
- European Commission
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Phylogenetic Studies
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
- Keywords
- European Nucleotide Archive, Sequence Read Archive, DNA sequence databases, sequence similarity search, European Genome-phenome Archive
- MeSH terms
- Base Sequence, Europe, Databases, Nucleic Acid, Molecular Sequence Annotation, 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.
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