دورية أكاديمية

Data reduction in protein serial crystallography

التفاصيل البيبلوغرافية
العنوان: Data reduction in protein serial crystallography
المؤلفون: Marina Galchenkova, Alexandra Tolstikova, Bjarne Klopprogge, Janina Sprenger, Dominik Oberthuer, Wolfgang Brehm, Thomas A. White, Anton Barty, Henry N. Chapman, Oleksandr Yefanov
المصدر: IUCrJ, Vol 11, Iss 2, Pp 190-201 (2024)
بيانات النشر: International Union of Crystallography, 2024.
سنة النشر: 2024
المجموعة: LCC:Crystallography
مصطلحات موضوعية: protein serial crystallography, data reduction, data compression, data quality evaluation, Crystallography, QD901-999
الوصف: Serial crystallography (SX) has become an established technique for protein structure determination, especially when dealing with small or radiation-sensitive crystals and investigating fast or irreversible protein dynamics. The advent of newly developed multi-megapixel X-ray area detectors, capable of capturing over 1000 images per second, has brought about substantial benefits. However, this advancement also entails a notable increase in the volume of collected data. Today, up to 2 PB of data per experiment could be easily obtained under efficient operating conditions. The combined costs associated with storing data from multiple experiments provide a compelling incentive to develop strategies that effectively reduce the amount of data stored on disk while maintaining the quality of scientific outcomes. Lossless data-compression methods are designed to preserve the information content of the data but often struggle to achieve a high compression ratio when applied to experimental data that contain noise. Conversely, lossy compression methods offer the potential to greatly reduce the data volume. Nonetheless, it is vital to thoroughly assess the impact of data quality and scientific outcomes when employing lossy compression, as it inherently involves discarding information. The evaluation of lossy compression effects on data requires proper data quality metrics. In our research, we assess various approaches for both lossless and lossy compression techniques applied to SX data, and equally importantly, we describe metrics suitable for evaluating SX data quality.
نوع الوثيقة: article
وصف الملف: electronic resource
اللغة: English
تدمد: 2052-2525
20522525
Relation: http://scripts.iucr.org/cgi-bin/paper?S205225252400054X; https://doaj.org/toc/2052-2525
DOI: 10.1107/S205225252400054X
URL الوصول: https://doaj.org/article/7172b08f189341d2b6450e8be4c657b5
رقم الأكسشن: edsdoj.7172b08f189341d2b6450e8be4c657b5
قاعدة البيانات: Directory of Open Access Journals
الوصف
تدمد:20522525
DOI:10.1107/S205225252400054X