| Autor: |
Brinda Vallat, Gerardo Tauriello, Stefan Bienert, Juergen Haas, Benjamin M. Webb, Augustin Žídek, Wei Zheng, Ezra Peisach, Dennis W. Piehl, Ivan Anischanka, Ian Sillitoe, James Tolchard, Mihaly Varadi, David Baker, Christine Orengo, Yang Zhang, Jeffrey C. Hoch, Genji Kurisu, Ardan Patwardhan, Sameer Velankar, Stephen K. Burley, Andrej Sali, Torsten Schwede, Helen M. Berman, John D. Westbrook |
| Rok vydání: |
2022 |
| Předmět: |
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| DOI: |
10.1101/2022.12.06.518550 |
| Popis: |
ModelCIF (github.com/ihmwg/ModelCIF) is a data information framework developed for and by computational structural biologists to enable delivery ofFindable, Accessible, Interoperable, andReusable(FAIR) data to users worldwide. It is an extension of the Protein Data Bank Exchange / macromolecular Crystallographic Information Framework (PDBx/mmCIF), which is the global data standard for representing experimentally-determined, three-dimensional (3D) structures of macromolecules and associated metadata. ModelCIF provides an extensible data representation for deposition, archiving, and public dissemination of predicted 3D models of proteins. The PDBx/mmCIF framework and its extensions (e.g., ModelCIF) are managed by the Worldwide Protein Data Bank partnership (wwPDB,wwpdb.org) in collaboration with relevant community stakeholders such as the wwPDB ModelCIF Working Group (wwpdb.org/task/modelcif). This semantically rich and extensible data framework for representing computed structure models (CSMs) accelerates the pace of scientific discovery. Herein, we describe the architecture, contents, and governance of ModelCIF, and tools and processes for maintaining and extending the data standard. Community tools and software libraries that support ModelCIF are also described. |
| Databáze: |
OpenAIRE |
| Externí odkaz: |
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