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Cited by 0Advanced Electron Microscopy Techniques and ApplicationsData Visualization and AnalyticsResearch Data Management Practices

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Chart builder: an interactive tool for user driven data visualization in the electron microscopy data bank

Open access
Fonseca, Neli, Duraisamy, Amudha Kumari, Wang, Zhe, Somasundharam, Sriram, Tayebinia, Minoosadat, de Oliveira, Lucas C., Ma, Miao, Turner, Jack, Patwardhan, Ardan, Kleywegt, Gerard J., Hartley, Matthew, Morris, Kyle L.·2026·Frontiers in Bioinformatics
DOI 10.3389/fbinf.2026.1763403PMC PMC13002805

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Abstract

The cryogenic sample-electron microscopy (cryoEM) field has generated significant amounts of 3D Electron Microscopy (3DEM) volumetric data and associated metadata, now comprehensively archived in the Electron Microscopy Data Bank (EMDB - www.emdatabank.org ) and the Electron Microscopy Public Image Archive (EMPIAR - www.empiar.org ). Harnessing the full potential of these resources requires robust, flexible, and publicly accessible tools for data exploration, analysis and retrieval. Here, we present Chart Builder, an interactive web-based platform that enables researchers to create customizable, publication-quality visualizations directly from archival metadata, validation assessments, and cross-reference annotations. Chart Builder integrates the same query-driven and flexible Solr search system as EMDB search, into a user interface with tools to assist users to filter, group, and compare data without programming expertise. It supports multiple chart types (including line, bar, area, scatter (2D and 3D), histogram, bubble, pie, geographic and Venn diagrams) with customizable axes, data series, and statistical operators. Users can apply global filters, define temporal, categorical, or custom query-based axes, and explore multi-dimensional relationships interactively. Chart data-points are linked to their underlying datasets, such that visualisation interaction opens entry-level or archive-level search results for inspection and datasets from charts may be exported in several ways. Findability, accessibility, interoperability and reusability of data are facilitated by these direct access and export mechanisms, including HTML embedding, persistent URL sharing and chart/data download options. By combining interactivity and ease of use with up-to-date access to the EMDB and EMPIAR archive metadata, both computational and experimental communities may explore and visualize current metadata and export to formats for further analysis or as publication-ready figures. Chart Builder promotes community-driven data analysis and empowers users to evaluate trends in the biological 3DEM field. Chart Builder is freely accessible and fully integrated into the EMDB website at https://www.ebi.ac.uk/emdb/statistics/builder/ .

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Research works printed but not linked: 38

  1. Afonine, 2018, New tools for the analysis and validation of cryo-EM maps and atomic models, Acta Crystallogr. D. Struct. Biol., 74, 814, 10.1107/s2059798318009324 · DOI
  2. Aleksander, 2023, The gene ontology knowledgebase in 2023, Genetics, 224, iyad031, 10.1093/genetics/iyad031 · DOI
  3. Andreeva, 2020, The SCOP database in 2020: expanded classification of representative family and superfamily domains of known protein structures, Nucleic Acids Research, 48, D376, 10.1093/nar/gkz1064 · DOI
  4. Chen, 2013, High-resolution noise substitution to measure overfitting and validate resolution in 3D structure determination by single particle electron cryomicroscopy, Ultramicroscopy, 135, 24, 10.1016/j.ultramic.2013.06.004 · DOI
  5. Duraisamy, 2025, EMICSS: added-value annotations for EMDB entries, Bioinforma. Adv., 5, vbaf203, 10.1093/bioadv/vbaf203 · DOI
  6. Haak, 2012, ORCID: a system to uniquely identify researchers, Learn. Publishing, 25, 259, 10.1087/20120404 · DOI
  7. Hastings, 2016, ChEBI in 2016: improved services and an expanding collection of metabolites, Nucleic Acids Research, 44, D1214, 10.1093/nar/gkv1031 · DOI · Paper page
  8. Iudin, 2023, EMPIAR: the electron microscopy public image archive, Nucleic Acids Res., 51, D1503, 10.1093/nar/gkac1062 · DOI
  9. Joseph, 2017, Improved metrics for comparing structures of macromolecular assemblies determined by 3D electron-microscopy, J. Structural Biology, 199, 12, 10.1016/j.jsb.2017.05.007 · DOI
  10. Kalvari, 2021, Rfam 14: expanded coverage of metagenomic, viral and microRNA families, Nucleic Acids Research, 49, D192, 10.1093/nar/gkaa1047 · DOI
  11. Kimanius, 2024, Data-driven regularization lowers the size barrier of cryo-EM structure determination, Nat. Methods, 21, 1216, 10.1038/s41592-024-02304-8 · DOI
  12. Knox, 2024, DrugBank 6.0: the DrugBank knowledgebase for 2024, Nucleic Acids Research, 52, D1265, 10.1093/nar/gkad976 · DOI
  13. Kühlbrandt, 2014, The resolution revolution, Science, 343, 1443, 10.1126/science.1251652 · DOI · Paper page
  14. Lagerstedt, 2013, Web-based visualisation and analysis of 3D electron-microscopy data from EMDB and PDB, J. Structural Biology, 184, 173, 10.1016/j.jsb.2013.09.021 · DOI
  15. Lawson, 2021, Cryo-EM model validation recommendations based on outcomes of the 2019 EMDataResource challenge, Nat. Methods, 18, 156, 10.1038/s41592-020-01051-w · DOI
  16. Liebschner, 2019, Macromolecular structure determination using X-rays, neutrons and electrons: recent developments in Phenix, Biol. Crystallogr., 75, 861, 10.1107/S2059798319011471 · DOI · Paper page
  17. Meldal, 2015, The complex portal-an encyclopaedia of macromolecular complexes, Nucleic Acids Research, 43, D479, 10.1093/nar/gku975 · DOI
  18. Mistry, 2021, Pfam: the protein families database in 2021, Nucleic Acids Research, 49, D412, 10.1093/nar/gkaa913 · DOI · Paper page
  19. Patwardhan, 2017, Building bridges between cellular and molecular structural biology, Elife, 6, e25835, 10.7554/eLife.25835 · DOI
  20. Paysan-Lafosse, 2023, InterPro in 2022, Nucleic Acids Research, 51, D418, 10.1093/nar/gkac993 · DOI
  21. 2022, PDBe-KB: collaboratively defining the biological context of structural data, Nucleic Acids Res., 50, D534, 10.1093/nar/gkab988 · DOI · Paper page
  22. Pintilie, 2020, Measurement of atom resolvability in cryo-EM maps with Q-scores, Nat. Methods, 17, 328, 10.1038/s41592-020-0731-1 · DOI
  23. Punjani, 2017, cryoSPARC: algorithms for rapid unsupervised cryo-EM structure determination, Nat. Methods, 14, 290, 10.1038/nmeth.4169 · DOI · Paper page
  24. 2024, Research Organization registry, Res. Organ. Registry
  25. Rosonovski, 2024, Europe PMC in 2023, Nucleic Acids Res., 52, D1668, 10.1093/nar/gkad1085 · DOI
  26. Sehnal, 2021, Mol Viewer: modern web app for 3D visualization and analysis of large biomolecular structures, Nucleic Acids Res., 49, W431, 10.1093/nar/gkab314 · DOI · Paper page
  27. Sillitoe, 2021, CATH: increased structural coverage of functional space, Nucleic Acids Research, 49, D266, 10.1093/nar/gkaa1079 · DOI · Paper page
  28. Tagari, 2002, New electron microscopy database and deposition system, Trends Biochemical Sciences, 27, 589, 10.1016/s0968-0004(02)02176-x · DOI
  29. 2025, UniProt: the universal protein knowledgebase in 2025, Nucleic Acids Res., 53, D609, 10.1093/nar/gkae1010 · DOI · Paper page
  30. Varadi, 2022, AlphaFold Protein Structure Database: massively expanding the structural coverage of protein-sequence space with high-accuracy models, Nucleic Acids Research, 50, D439, 10.1093/nar/gkab1061 · DOI · Paper page
  31. Velankar, 2016, PDBe: improved accessibility of macromolecular structure data from PDB and EMDB, Nucleic Acids Research, 44, D385, 10.1093/nar/gkv1047 · DOI
  32. Wang, 2022, Validation analysis of EMDB entries, Biol. Crystallogr., 78, 542, 10.1107/S205979832200328X · DOI
  33. Westbrook, 2022, PDBx/mmCIF ecosystem: foundational semantic tools for structural biology, J. Molecular Biology, 434, 167599, 10.1016/j.jmb.2022.167599 · DOI
  34. 2019, Protein Data Bank: the single global archive for 3D macromolecular structure data, Nucleic Acids Research, Nucleic Acids Res., 47, D520, 10.1093/nar/gky949 · DOI · Paper page
  35. 2024, EMDB—The electron microscopy data bank,, D456
  36. Young, 2017, OneDep: unified wwPDB system for deposition, biocuration, and validation of macromolecular structures in the PDB archive, Structure, 25, 536, 10.1016/j.str.2017.01.004 · DOI
  37. Zdrazil, 2024, The ChEMBL Database in 2023: a drug discovery platform spanning multiple bioactivity data types and time periods, Nucleic Acids Research, 52, D1180, 10.1093/nar/gkad1004 · DOI
  38. Zivanov, 2018, New tools for automated high-resolution cryo-EM structure determination in RELION-3, Elife. Nov., 7, e42166, 10.7554/eLife.42166 · DOI

Metadata

Authors
Fonseca, N., Duraisamy, A. K., Wang, Z., Somasundharam, S., Tayebinia, M., de Oliveira, L. C., Ma, M., Turner, J., Patwardhan, A., Kleywegt, G. J., Hartley, M., & Morris, K. L.
Affiliations
European Bioinformatics Institute (GB)
Corresponding author
Morris, Kyle L.
ORCID
Venue
Frontiers in Bioinformatics
Publisher
Frontiers Media SA
Published
2026-03-06
Volume
6
Pages
1763403-1763403
ISSN
2673-7647 (ISSN-L)
DOI
10.3389/fbinf.2026.1763403
PMC
PMC13002805
OpenAlex
W7134047437
Cited by
0
References
2
FWCI
0.00
Type
journal article
Language
en
Open access
Licence
Locations
  • Frontiers in Bioinformatics (publishedVersion, cc-by)
  • bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
  • European Bioinformatics Institute
  • Wellcome Trust (212977/Z/18/Z)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Structural Biology › Advanced Electron Microscopy Techniques and Applications
  • Physical Sciences › Computer Science › Computer Graphics and Computer-Aided Design › Data Visualization and Analytics
  • Physical Sciences › Computer Science › Information Systems › Research Data Management Practices
Keywords
EMPIAR, 3D electron microscopy, data visualization, interactive web tool, data archiving, publication-quality figures, data reusability, data interoperability

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