BinaryCIF and CIFTools-Lightweight, efficient and extensible macromolecular data management
Identifikátory výsledku
Kód výsledku v IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14740%2F20%3A00117701" target="_blank" >RIV/00216224:14740/20:00117701 - isvavai.cz</a>
Výsledek na webu
<a href="https://doi.org/10.1371/journal.pcbi.1008247" target="_blank" >https://doi.org/10.1371/journal.pcbi.1008247</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1371/journal.pcbi.1008247" target="_blank" >10.1371/journal.pcbi.1008247</a>
Alternativní jazyky
Jazyk výsledku
angličtina
Název v původním jazyce
BinaryCIF and CIFTools-Lightweight, efficient and extensible macromolecular data management
Popis výsledku v původním jazyce
3D macromolecular structural data is growing ever more complex and plentiful in the wake of substantive advances in experimental and computational structure determination methods including macromolecular crystallography, cryo-electron microscopy, and integrative methods. Efficient means of working with 3D macromolecular structural data for archiving, analyses, and visualization are central to facilitating interoperability and reusability in compliance with the FAIR Principles. We address two challenges posed by growth in data size and complexity. First, data size is reduced by bespoke compression techniques. Second, complexity is managed through improved software tooling and fully leveraging available data dictionary schemas. To this end, we introduce BinaryCIF, a serialization of Crystallographic Information File (CIF) format files that maintains full compatibility to related data schemas, such as PDBx/mmCIF, while reducing file sizes by more than a factor of two versus gzip compressed CIF files. Moreover, for the largest structures, BinaryCIF provides even better compression-factor ten and four versus CIF files and gzipped CIF files, respectively. Herein, we describe CIFTools, a set of libraries in Java and TypeScript for generic and typed handling of CIF and BinaryCIF files. Together, BinaryCIF and CIFTools enable lightweight, efficient, and extensible handling of 3D macromolecular structural data.
Název v anglickém jazyce
BinaryCIF and CIFTools-Lightweight, efficient and extensible macromolecular data management
Popis výsledku anglicky
3D macromolecular structural data is growing ever more complex and plentiful in the wake of substantive advances in experimental and computational structure determination methods including macromolecular crystallography, cryo-electron microscopy, and integrative methods. Efficient means of working with 3D macromolecular structural data for archiving, analyses, and visualization are central to facilitating interoperability and reusability in compliance with the FAIR Principles. We address two challenges posed by growth in data size and complexity. First, data size is reduced by bespoke compression techniques. Second, complexity is managed through improved software tooling and fully leveraging available data dictionary schemas. To this end, we introduce BinaryCIF, a serialization of Crystallographic Information File (CIF) format files that maintains full compatibility to related data schemas, such as PDBx/mmCIF, while reducing file sizes by more than a factor of two versus gzip compressed CIF files. Moreover, for the largest structures, BinaryCIF provides even better compression-factor ten and four versus CIF files and gzipped CIF files, respectively. Herein, we describe CIFTools, a set of libraries in Java and TypeScript for generic and typed handling of CIF and BinaryCIF files. Together, BinaryCIF and CIFTools enable lightweight, efficient, and extensible handling of 3D macromolecular structural data.
Klasifikace
Druh
J<sub>imp</sub> - Článek v periodiku v databázi Web of Science
CEP obor
—
OECD FORD obor
10608 - Biochemistry and molecular biology
Návaznosti výsledku
Projekt
Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.
Návaznosti
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Ostatní
Rok uplatnění
2020
Kód důvěrnosti údajů
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Údaje specifické pro druh výsledku
Název periodika
PLoS Computational Biology
ISSN
1553-734X
e-ISSN
1553-7358
Svazek periodika
16
Číslo periodika v rámci svazku
10
Stát vydavatele periodika
US - Spojené státy americké
Počet stran výsledku
13
Strana od-do
1-13
Kód UT WoS článku
000585163600006
EID výsledku v databázi Scopus
2-s2.0-85094682973