ArticlePLoS computational biology2017
MMTF-An efficient file format for the transmission, visualization, and analysis of macromolecular structures.
Article in PLoS computational biology, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.
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Who cites it
28 citing papers in PubMed.
- From wireframes to immersive reality: a historical perspective on molecular visualization software.Briefings in bioinformatics · 2026Review
- AI-Driven Variant Annotation for Precision Oncology in Breast Cancer.Clinical and translational science · 2025Article
- Visualizing and analyzing 3D biomolecular structures using Mol* at RCSB.org: Influenza A H5N1 virus proteome case study.Protein science : a publication of the Protein Society · 2025Article
- Efficient protein structure archiving using ProteStAr.Bioinformatics (Oxford, England) · 2024Article
- Article
- PoseBusters: AI-based docking methods fail to generate physically valid poses or generalise to novel sequences.Chemical science · 2024Article
- Prop3D: A flexible, Python-based platform for machine learning with protein structural properties and biophysical data.BMC bioinformatics · 2024Article
- Image-centric compression of protein structures improves space savings.BMC bioinformatics · 2023Article
- Biotite: new tools for a versatile Python bioinformatics library.BMC bioinformatics · 2023Article
- PDC: a highly compact file format to store protein 3D coordinates.Database : the journal of biological databases and curation · 2023Article
- Foldcomp: a library and format for compressing and indexing large protein structure sets.Bioinformatics (Oxford, England) · 2023Article
- PDBx/mmCIF Ecosystem: Foundational Semantic Tools for Structural Biology.Journal of molecular biology · 2022Review
- Adding hydrogen atoms to molecular models via fragment superimposition.Algorithms for molecular biology : AMB · 2022Article
- Mol* Viewer: modern web app for 3D visualization and analysis of large biomolecular structures.Nucleic acids research · 2021Article
- The Bio3D packages for structural bioinformatics.Protein science : a publication of the Protein Society · 2021Article
- Real-time structural motif searching in proteins using an inverted index strategy.PLoS computational biology · 2020Article
- High-performance macromolecular data delivery and visualization for the web.Acta crystallographica. Section D, Structural biology · 2020Article
- BinaryCIF and CIFTools-Lightweight, efficient and extensible macromolecular data management.PLoS computational biology · 2020Article
- DUBS: A Framework for DevelopingJournal of chemical information and modeling · 2020Article
- atomium-a Python structure parser.Bioinformatics (Oxford, England) · 2020Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
Recent advances in experimental techniques have led to a rapid growth in complexity, size, and number of macromolecular structures that are made available through the Protein Data Bank. This creates a challenge for macromolecular visualization and analysis. Macromolecular structure files, such as PDB or PDBx/mmCIF files can be slow to transfer, parse, and hard to incorporate into third-party software tools. Here, we present a new binary and compressed data representation, the MacroMolecular Transmission Format, MMTF, as well as software implementations in several languages that have been developed around it, which address these issues. We describe the new format and its APIs and demonstrate that it is several times faster to parse, and about a quarter of the file size of the current standard format, PDBx/mmCIF. As a consequence of the new data representation, it is now possible to visualize structures with millions of atoms in a web browser, keep the whole PDB archive in memory or parse it within few minutes on average computers, which opens up a new way of thinking how to design and implement efficient algorithms in structural bioinformatics. The PDB archive is available in MMTF file format through web services and data that are updated on a weekly basis.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.