Toward interoperable bioscience data
Open accessAbstract
To make full use of research data, the bioscience community needs to adopt technologies and reward mechanisms that support interoperability and promote the growth of an open 'data commoning' culture. Here we describe the prerequisites for data commoning and present an established and growing ecosystem of solutions using the shared 'Investigation-Study-Assay' framework to support that vision.
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“GEO SOFT [20], Sequence Read Archive (SRA) XML [21], ENCODE [22], modENCODE [23], and ISA-TAB [24].”
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“It is becoming a de-facto standard, with many tools (Including SEEK) adopting the ISA-Tab format for metadata exchange [29].”
MethodSelf-citationThe center for expanded data annotation and retrieval
Musen, M. A., Bean, C. A., Cheung, K., Dumontier, M., Durante, K., Gevaert, O., Gonzalez-Beltran, A. N., Khatri, P., Kleinstein, S. H., O’Connor, M. J., et al. (2015) · Journal of the American Medical Informatics Association · doi:10.1093/jamia/ocv048 · Cited by 111 · see citing works
“50 standards,(5) such as BioSharing,(6) offer important resources not only to biomedical researchers, but also to journal editors and to biomedical curators who seek guidance regarding which standards to use.(7) Despite a growing set of guidelines and templates for defining metadata and numerous ontologies from”
BackgroundSelf-citationHow should the completeness and quality of curated nanomaterial data be evaluated?
Robinson, R. M., Lynch, I., Peijnenburg, W. J. G. M., Rumble, J., Klaessig, F., Marquardt, C., Rauscher, H., Puzyn, T., Purian, R., Åberg, C., et al. (2016) · Nanoscale · doi:10.1039/c5nr08944a · Cited by 110 · see citing works
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The Consortium of Metabolomics Studies (COMETS): Metabolomics in 47 Prospective Cohort Studies
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eNanoMapper: harnessing ontologies to enable data integration for nanomaterial risk assessment
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“ISA-TAB is a commonly used format for representing experimental data in structured tab-separated files [31].”
MethodSelf-citationData 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
“org [58, 97].”
e!DAL - a framework to store, share and publish research data
Arend, D., Lange, M., Chen, J., Colmsee, C., Flemming, S., Hecht, D., & Scholz, U. (2014) · BMC Bioinformatics · doi:10.1186/1471-2105-15-214 · Cited by 103 · see citing works
“Metadata standards [7] and data-exchange formats have been developed [8], and data warehouse infrastructures have been implemented [9].”
BackgroundGeneLab: Omics database for spaceflight experiments
Ray, S., Gebre, S., Fogle, H. W., Berrios, D. C., Tran, P. B., Galazka, J. M., & Costes, S. V. (2018) · Bioinformatics · doi:10.1093/bioinformatics/bty884 · Cited by 100 · see citing works
ISA-TAB-Nano: A Specification for Sharing Nanomaterial Research Data in Spreadsheet-based Format
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“Many XML-based and spreadsheet-based data exchange formats have been successfully developed and adopted across the biomedical community; examples include the SBML – Systems Biology Markup Language [12]; BioPAX – Biological Pathway Exchange [13]; MAGE-ML – Microarray and Gene Expression Markup Language [14]; MAGE-TAB –…”
MethodInfluentialWang, M., Song, W., Chen, M., Wang, Q., Zhou, X., Xu, P., Krek, A., Yoon, Y., Ho, L., Orr, M. E., et al. (2022) · Molecular Neurodegeneration · doi:10.1186/s13024-022-00517-z · Cited by 100 · see citing works
Making Big Data Useful for Health Care: A Summary of the Inaugural MIT Critical Data Conference
Badawi, O., Brennan, T., Celi, L. A., Feng, M., Ghassemi, M., Ippolito, A., Johnson, A. E. W., Mark, R. G., Mayaud, L., Moody, G. B., et al. (2014) · JMIR Medical Informatics · doi:10.2196/medinform.3447 · Cited by 95 · see citing works
“These will likely include the creation of open-access genomic and clinical databases, use of a common scientific language [25] and (open) data access tools.”
The metaRbolomics Toolbox in Bioconductor and beyond
Stanstrup, J., Broeckling, C. D., Helmus, R., Hoffmann, N., Mathé, E. A., Naake, T., Nicolotti, L., Peters, K., Rainer, J., Salek, R. M., et al. (2019) · Metabolites · doi:10.3390/metabo9100200 · Cited by 91 · see citing works
“MetaDB supports both LC-MS and GC-MS datasets and offers a wide range of functionalities, including: data storage and metadata management (using the ISA-Tab format and ISACreator tool [300,301]), peak picking and annotation (via metaMS, an xcms and CAMERA add-on) and QC plots.”
MethodSelf-citationHuman cancer databases (Review)
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Data Sharing For Precision Medicine: Policy Lessons And Future Directions
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The Increasing Urgency for Standards in Basic Biologic Research
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Computational Drug Repurposing: Current Trends
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MetaboLights: towards a new COSMOS of metabolomics data management
Steinbeck, C., Conesa, P., Haug, K., Mahendraker, T., Williams, M., Maguire, E., Rocca‐Serra, P., Sansone, S., Salek, R. M., & Griffin, J. L. (2012) · Metabolomics · doi:10.1007/s11306-012-0462-0 · Cited by 87 · see citing works
Self-citationAgBioData consortium recommendations for sustainable genomics and genetics databases for agriculture
Harper, L., Campbell, J., Cannon, E. K. S., Jung, S., Poelchau, M., Walls, R., Andorf, C., Arnaud, E., Berardini, T., Birkett, C., et al. (2018) · Database J. Biol. Databases Curation · doi:10.1093/database/bay088 · Cited by 91 · see citing works
“org/) (49) approach to metadata is structured with three elements: the Investigation—the research context; a Study—a unit of research; and an Assay—an analytical measurement.”
Consent Codes: Upholding Standard Data Use Conditions
Dyke, S. O. M., Philippakis, A., Rambla, J., Paltoo, D. N., Luetkemeier, E. S., Knoppers, B. M., Brookes, A. J., Spalding, D., Thompson, M., Roos, M., et al. (2016) · PLoS Genetics · doi:10.1371/journal.pgen.1005772 · Cited by 82 · see citing works
“manuscript in preparation) [18]; (ii) ISA (Investigation, Study, Assay), a model for capturing research information originally for submission to EBI repositories [19]; (iii) research objects, a mechanism to bundle and annotate any kind of artefact related to an experiment [20]; and (iv) nanopublication, a newly develo…”
MethodOn behalf of the Brotman Baty Institute Mutational Scanning Working Group, Gelman, H., Dines, J. N., Berg, J., Berger, A. H., Brnich, S., Hisama, F. M., James, R. G., Rubin, A. F., Shendure, J., et al. (2019) · Genome Medicine · doi:10.1186/s13073-019-0698-7 · Cited by 81 · see citing works
Integrating imaging and omics data: A review
Antonelli, L., Guarracino, M. R., Maddalena, L., & Sangiovanni, M. (2019) · Biomedical Signal Processing and Control · doi:10.1016/j.bspc.2019.04.032 · Cited by 81 · 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
DATS, the data tag suite to enable discoverability of datasets
Sansone, S., Gonzalez-Beltran, A. N., Rocca‐Serra, P., Alter, G. C., Grethe, J. S., Xu, H., Fore, I., Lyle, J. A., Gururaj, A. E., Chen, X., et al. (2017) · Scientific Data · doi:10.1038/sdata.2017.59 · Cited by 76 · see citing works
Self-citationVempati, U. D., Chung, C., Mader, C. C., Koleti, A., Datar, N., Vidović, D., Wrobel, D., Erickson, S. D., Muhlich, J. L., Berriz, G. F., et al. (2014) · SLAS DISCOVERY · doi:10.1177/1087057114522514 · Cited by 75 · see citing works
Self-citationOntology-Based Querying with Bio2RDF’s Linked Open Data
Callahan, A., Cruz-Toledo, J., & Dumontier, M. (2013) · Journal of Biomedical Semantics · doi:10.1186/2041-1480-4-s1-s1 · Cited by 73 · see citing works
“Several approaches for integrating biological data have been reported [15-17], but they rely on a variety of data formats and standards, making sustainable large-scale integration challenging [18].”
BackgroundMicro-computed tomography for natural history specimens: a handbook of best practice protocols
Keklikoglou, K., Faulwetter, S., Chatzinikolaou, E., Wils, P., Brecko, J., Kvaček, J., Metscher, B., & Arvanitidis, C. (2019) · European Journal of Taxonomy · doi:10.5852/ejt.2019.522 · Cited by 72 · see citing works
FANTOM5 transcriptome catalog of cellular states based on Semantic MediaWiki
Abugessaisa, I., Shimoji, H., Şahin, S., Kondo, A., Harshbarger, J., Lizio, M., Hayashizaki, Y., Carninci, P., Forrest, A., Kasukawa, T., et al. (2016) · Database J. Biol. Databases Curation · doi:10.1093/database/baw105 · Cited by 73 · see citing works
“MAGE-tab (25) and ISA-tab (26) are accepted as standard formats for metadata describing experiments in functional genomics and other ‘–omics’ research.”
BackgroundFood Safety in the Age of Next Generation Sequencing, Bioinformatics, and Open Data Access
Taboada, E. N., Graham, M., Carriço, J. A., & Domselaar, G. V. (2017) · Frontiers in Microbiology · doi:10.3389/fmicb.2017.00909 · Cited by 71 · see citing works
“Alltheseefforts for standardization should contribute to a future in which data exchange may seamlessly occur, and truly interoperable resources may be created and shared (Sansone et al., 2012).”
BackgroundGigaDB: announcing the GigaScience database
Sneddon, T. P., Li, P., & Edmunds, S. (2012) · GigaScience · doi:10.1186/2047-217x-1-11 · Cited by 71 · see citing works
“Taking such a broad range of data types makes data interoperability an issue, and we have been working with the ISA-Commons community to see if Giga DB can capture study and assay metadata along with relationships between dataset components and take submissions using their ISA-Tab format [10].”
MethodSelf-citationBrown, 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
Self-citationTaxonomy-Based Glyph Design—with a Case Study on Visualizing Workflows of Biological Experiments
Maguire, E., Rocca‐Serra, P., Sansone, S., Davies, J., & Chen, M. (2012) · IEEE Transactions on Visualization and Computer Graphics · doi:10.1109/tvcg.2012.271 · Cited by 71 · see citing works
Self-citationThe FaceBase Consortium: A comprehensive resource for craniofacial researchers
Brinkley, J. F., Fisher, S., Harris, M. P., Holmes, G., Hooper, J. E., Jabs, E. W., Jones, K. L., Kesselman, C., Klein, O. D., Maas, R. L., et al. (2016) · Development · doi:10.1242/dev.135434 · Cited by 67 · see citing works
“A unified experimental data model based on the widely used ISA-TAB format (Sansone et al., 2012) leverages OCDM to provide structure to the data and to enable rapid discovery.”
mzTab-M: A Data Standard for Sharing Quantitative Results in Mass Spectrometry Metabolomics
Hoffmann, N., Rein, J., Sachsenberg, T. T., Hartler, J., Haug, K., Mayer, G., Alka, O., Dayalan, S., Pearce, J. T. M., Rocca‐Serra, P., et al. (2019) · Analytical Chemistry · doi:10.1021/acs.analchem.8b04310 · Cited by 66 · see citing works
Self-citationEukaryotic diversity at pH extremes
Amaral‐Zettler, L. (2013) · Frontiers in Microbiology · doi:10.3389/fmicb.2012.00441 · Cited by 66 · see citing works
“The open source investigation/study/assay (Sansone et al., 2012) metadata-tracking framework was used to curate the datasets and format them for submission to the NCBI sequence read archive (SRA) database under the SRA number SRA059386.”
MethodSelf-citationA sea of standards for omics data: sink or swim?
Tenenbaum, J. D., Sansone, S., & Haendel, M. A. (2013) · Journal of the American Medical Informatics Association · doi:10.1136/amiajnl-2013-002066 · Cited by 65 · see citing works
Self-citationlinkedISA: semantic representation of ISA-Tab experimental metadata
Gonzalez-Beltran, A. N., Maguire, E., Sansone, S., & Rocca‐Serra, P. (2014) · BMC Bioinformatics · doi:10.1186/1471-2105-15-s14-s4 · Cited by 62 · see citing works
“The framework is used by an expanding community, the ISA Commons [18] to deliver a growing ecosystem of public and internal resources - in increasingly diverse set of life science and biomedical domains – ranging from international public repositories [19], institutional repositories [20] to funded research consortia…”
MethodSelf-citationTracking materials science data lineage to manage millions of materials experiments and analyses
Soedarmadji, E., Stein, H. S., Suram, S. K., Guevarra, D., & Gregoire, J. M. (2019) · npj Computational Materials · doi:10.1038/s41524-019-0216-x · Cited by 59 · see citing works
Стоев, П., Komerički, A., Akkari, N., Liu, S., Zhou, X. Y., Weigand, A. M., Hostens, J., Hunter, C., Edmunds, S., Porco, D., et al. (2013) · Biodiversity Data Journal · doi:10.3897/bdj.1.e1013 · Cited by 57 · see citing works
Self-citationScaling-up metabolomics: Current state and perspectives
Hajjar, G., Santos, M. C. B., Bertrand‐Michel, J., Canlet, C., Castelli, F. A., Creusot, N., Déchaumet, S., Diémé, B., Giacomoni, F., Giraudeau, P., et al. (2023) · TrAC Trends in Analytical Chemistry · doi:10.1016/j.trac.2023.117225 · Cited by 54 · see citing works
The MetaboLights repository: curation challenges in metabolomics
Salek, R. M., Haug, K., Conesa, P., Hastings, J., Williams, M., Mahendraker, T., Maguire, E., Gonzalez-Beltran, A. N., Rocca‐Serra, P., Sansone, S., et al. (2013) · Database · doi:10.1093/database/bat029 · Cited by 54 · see citing works
“These include sample preparation and extraction protocols, instrument-related parameters and related metadata, all of which comply with the ‘Metabolomics Standards Initiative’ (MSI) reporting recommendations (8, 9).”
MethodInfluentialSelf-citationKinetic modeling of cell metabolism for microbial production
Costa, R. S., Hartmann, A., & Vinga, S. (2015) · Journal of Biotechnology · doi:10.1016/j.jbiotec.2015.12.023 · Cited by 53 · see citing works
Deep learning in systems medicine
Wang, H., Pujos‐Guillot, E., Comte, B., de Miranda, J. L., Spiwok, V., Chorbev, I., Castiglione, F., Tieri, P., Watterson, S., McAllister, R., et al. (2020) · Briefings in Bioinformatics · doi:10.1093/bib/bbaa237 · Cited by 53 · see citing works
“This challenging task requires minimal reporting guidelines, formats and standards for data management that have been set up in an open science research perspective [27, 28].”
BackgroundNASA GeneLab RNA-seq consensus pipeline: Standardized processing of short-read RNA-seq data
Overbey, E. G., Saravia-Butler, A., Zhang, Z., Rathi, K. S., Fogle, H. W., da Silveira, W. A., Barker, R. J., Bass, J. J., Beheshti, A., Berrios, D. C., et al. (2021) · iScience · doi:10.1016/j.isci.2021.102361 · Cited by 52 · see citing works
Data management and best practice for plant science
Leonelli, S., Davey, R., Arnaud, E., Parry, G., & Bastow, R. (2017) · Nature Plants · doi:10.1038/nplants.2017.86 · Cited by 51 · see citing works
Food authentication in real life: How to link nontargeted approaches with routine analytics?
Creydt, M., & Fischer, M. J. (2020) · Electrophoresis · doi:10.1002/elps.202000030 · Cited by 51 · see citing works
PLANTdataHUB : a collaborative platform for continuous FAIR data sharing in plant research
Weil, H. L., Schneider, K., Tschöpe, M., Bauer, J., Maus, O., Frey, K., Brilhaus, D., Rodrigues, C. M., Doniparthi, G., Wetzels, F., et al. (2023) · The Plant Journal · doi:10.1111/tpj.16474 · Cited by 50 · see citing works
Biospecimens, biomarkers, and burgeoning data: the imperative for more rigorous research standards
Poste, G. H. (2012) · Trends in Molecular Medicine · doi:10.1016/j.molmed.2012.09.003 · Cited by 50 · see citing works
The Plant Ontology: A Tool for Plant Genomics
Cooper, L., & Jaiswal, P. (2015) · Methods in molecular biology · doi:10.1007/978-1-4939-3167-5_5 · Cited by 50 · see citing works
OntoMaton: a Bioportal powered ontology widget for Google Spreadsheets
Maguire, E., Gonzalez-Beltran, A. N., Whetzel, P. L., Sansone, S., & Rocca‐Serra, P. (2012) · Bioinformatics · doi:10.1093/bioinformatics/bts718 · Cited by 50 · see citing works
“While ontology-enabled standalone tools exist (Rocca-Serra et al ., 2011; Wolstencroft et al ., 2011), they lack collaborative features.”
Self-citationWaltemath, D., & Wolkenhauer, O. (2016) · IEEE Transactions on Biomedical Engineering · doi:10.1109/tbme.2016.2555481 · Cited by 49 · see citing works
“BioSharing [79] is a catalogue of standards, minimum information guidelines, and formats for the biosciences.”
BackgroundGlobal open data management in metabolomics
Haug, K., Salek, R. M., & Steinbeck, C. (2017) · Current Opinion in Chemical Biology · doi:10.1016/j.cbpa.2016.12.024 · Cited by 48 · see citing works
Self-citationBread matters: a national initiative to profile the genetic diversity of Australian wheat
Edwards, D., Wilcox, S., Barrero, R. A., Fleury, D., Cavanagh, C. R., Forrest, K., Hayden, M., Moolhuijzen, P., Keeble‐Gagnère, G., Bellgard, M., et al. (2012) · Plant Biotechnology Journal · doi:10.1111/j.1467-7652.2012.00717.x · Cited by 48 · see citing works
“…are used in building genetic resources such as genetic populations or biotechnologies (parental lines and transformation); and they are key varieties that are both internationally studied and relevant to research in Australia (Rocca-Serra et al., 2010; Sansone et al., 2012; Taylor et al., 2008).”
BackgroundMethodSelf-citationZingone, A., Harrison, P. J. H., Kraberg, A. C., Lehtinen, S., McQuatters‐Gollop, A., O’Brien, T., Sun, J., & Jakobsen, H. H. (2015) · Estuarine Coastal and Shelf Science · doi:10.1016/j.ecss.2015.05.024 · Cited by 48 · see citing works
BRIDGE – A Visual Analytics Web Tool for Barley Genebank Genomics
König, P., Beier, S., Basterrechea, M., Schüler, D., Arend, D., Mascher, M., Stein, N., Scholz, U., & Lange, M. (2020) · Frontiers in Plant Science · doi:10.3389/fpls.2020.00701 · Cited by 48 · see citing works
“Beside the export of genetic information via VCF files, it is also possible to export the phenotypic data records in the ISA-Tab format (Sansone et al., 2012), which combines a machine-readable and a textual human-readable representation ( Figure 4J ).”
BackgroundMethodImproving data and knowledge management to better integrate health care and research
Cases, M., Furlong, L. I., Albanell, J., Altman, R. B., Bellazzi, R., Boyer, S. K., Brand, A. M., Brookes, A. J., Brunak, S., Clark, T., et al. (2013) · Journal of Internal Medicine · doi:10.1111/joim.12105 · Cited by 47 · see citing works
“Efforts to better structure scientific knowledge, for instance, by means of nanopublications [5] or the Investigation Study Assay (ISA) commons [6], could provide key components of this solution.”
BackgroundSelf-citationBest practice data life cycle approaches for the life sciences
Griffin, P. C., Khadake, J. R., Lemay, K. S., Lewis, S., Orchard, S. E., Pask, A. J., Pope, B. J., Roessner, U., Russell, K., Seemann, T., et al. (2017) · F1000Research · doi:10.12688/f1000research.12344.2 · Cited by 47 · see citing works
Principles of metadata organization at the ENCODE data coordination center
Hong, E. L., Sloan, C. A., Chan, E. T., Davidson, J. M., Malladi, V. S., Strattan, J. S., Hitz, B. C., Gabdank, I., Narayanan, A. K., Ho, M., et al. (2016) · Database · doi:10.1093/database/baw001 · Cited by 46 · see citing works
“The ENCODE metadata, however, can be exported in ISA-TAB, GEO, SRA-XML or GA4GH-defined formats.”
MethodColetta, A., Molter, C., Duqué, R., Steenhoff, D., Taminau, J., de Schaetzen, V., Meganck, S., Lazar, C., Venet, D., Detours, V., et al. (2012) · Genome biology · doi:10.1186/gb-2012-13-11-r104 · Cited by 45 · see citing works
“example, the Unified Medical Language System (UMLS) [64]), as well as more general, bioscience-oriented data-exchange formats that are currently in active development [65].”
Background
- Authors
- Sansone, S.-A., Rocca-Serra, P., Field, D., Maguire, E., Taylor, C., Hofmann, O., Fang, H., Neumann, S., Tong, W., Amaral-Zettler, L., Begley, K., Booth, T., Bougueleret, L., Burns, G., Chapman, B., Clark, T., Coleman, L.-A., Copeland, J., Das, S., de Daruvar, A., de Matos, P., Dix, I., Edmunds, S., Evelo, C. T., Forster, M. J., Gaudet, P., Gilbert, J., Goble, C., Griffin, J. L., Jacob, D., Kleinjans, J., Harland, L., Haug, K., Hermjakob, H., Sui, S. J. H., Laederach, A., Liang, S., Marshall, S., McGrath, A., Merrill, E., Reilly, D., Roux, M., Shamu, C. E., Shang, C. A., Steinbeck, C., Trefethen, A., Williams-Jones, B., Wolstencroft, K., Xenarios, I., & Hide, W.
- Affiliations
- University of Oxford (GB)
- Natural Environment Research Council (GB)
- European Bioinformatics Institute (GB)
- Harvard University (US)
- National Center for Toxicological Research (US)
- Leibniz Institute of Plant Biochemistry (DE)
- Ontario Institute for Cancer Research (CA)
- SIB Swiss Institute of Bioinformatics (CH)
- University of Southern California (US)
- British Library (GB)
- AstraZeneca (United Kingdom) (GB)
- BGI Group (China) (CN)
- Netherlands Bioinformatics Centre (NL)
- Syngenta (United Kingdom) (GB)
- Northwestern University (US)
- Argonne National Laboratory (US)
- University of Manchester (GB)
- MRC Elsie Widdowson Laboratory (GB)
- Université de Bordeaux (FR)
- Maastricht University (NL)
- University of North Carolina at Chapel Hill (US)
- Commonwealth Scientific and Industrial Research Organisation (AU)
- Massachusetts General Hospital (US)
- Bioplatforms Australia (AU)
- Corresponding author
- Sansone, Susanna-Assunta
- ORCID
- Sansone, Susanna-Assunta
- Maguire, Eamonn
- Taylor, Chris
- Hofmann, Oliver
- Fang, Hong
- Neumann, Steffen
- Tong, Weida
- Begley, Kimberly
- Booth, Tim
- Burns, Gully
- Chapman, Brad
- Clark, Tim
- Coleman, Lee-Ann
- Das, Sudeshna
- Edmunds, Scott
- Evelo, Chris T
- Gaudet, Pascale
- Gilbert, Jack
- Goble, Carole
- Griffin, Julian L
- Jacob, Daniel
- Kleinjans, Jos
- Harland, Lee
- Hermjakob, Henning
- Sui, Shannan J Ho
- Laederach, Alain
- McGrath, Annette
- Merrill, Emily
- Reilly, Dorothy
- Shamu, Caroline E
- Shang, Catherine A
- Steinbeck, Christoph
- Williams-Jones, Bryn
- Wolstencroft, Katherine
- Venue
- Nature Genetics
- Published
- 2012-01-27
- Volume
- 44
- Issue
- 2
- Pages
- 121-126
- ISSN
- 1061-4036 (ISSN-L)
- 1546-1718
- PMC
- PMC3428019
- OpenAlex
- W2141297584
- Cited by
- 475
- References
- 29
- Citations by year
- 2026: 20 · 2025: 20 · 2024: 42 · 2023: 22 · 2022: 30 · 2021: 31 · 2020: 33 · 2019: 38 · 2018: 28 · 2017: 34 · 2016: 25 · 2015: 33 · 2014: 39 · 2013: 37 · 2012: 38
- FWCI
- 130.22
- Type
- journal article
- Language
- en
- Open access
- hybrid
- doi.org
- Licence
- Locations
- Nature Genetics (publishedVersion, cc-by-nc-sa)
- PubMed (publishedVersion)
- Research Publications (Maastricht University) (publishedVersion, cc-by-nc-sa)
- PubMed Central (acceptedVersion)
- HAL (submittedVersion)
- Open Access Server of the Woods Hole Scientific Community (Woods Hole Scientific Community) (submittedVersion, cc-by-nc-sa)
- IRIS (submittedVersion)
- NERC Open Research Archive (Natural Environment Research Council) (submittedVersion)
- Research Explorer (The University of Manchester) (submittedVersion)
- SERVAL (Université de Lausanne) (submittedVersion)
- Research Publications (Maastricht University) (submittedVersion, other-oa)
- Funders
- National Institutes of Health (5u54hg006097-03, 5u24rr025736-02)
- Biotechnology and Biological Sciences Research Council (BB/I000917/1, BB/E025080/1, BB/I000860/1, BB/H024921/1, BB/I000771/1, BB/I000933/1, BB/G010218/1, BB/I004637/1, BB/I025840/1, BB/D006422/1)
- National Heart, Lung, and Blood Institute (R01HL111527)
- National Institute of Mental Health (R21MH087336)
- National Human Genome Research Institute (U54-HG006097)
- National Cancer Institute (RC2CA148222)
- National Institute of General Medical Sciences (R00GM079953, U24GM104203, R01GM101237, R01GM083871)
- National Center for Research Resources (S10RR031865, U24-RR025736)
- Topics
- Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
- Social Sciences › Decision Sciences › Information Systems and Management › Scientific Computing and Data Management
- Social Sciences › Decision Sciences › Information Systems and Management › Interdisciplinary Research and Collaboration
- Keywords
- research data sharing, data ecosystems
- MeSH terms
- Information Storage and Retrieval, Biomedical Research
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 ›
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