Abstract
Mass spectrometry is used to sequence proteins and extract bio-markers of biological environments. These bio-markers can be used to diagnose thousands of diseases and optimize biological environments such as bio-gas plants. Indexing of the protein sequence data allows to streamline the experiments and speed up the analysis. In our work, we present a schema for distributed column-based database management systems using a column-oriented index to store sequence data. This leads to the problem, how to transform the protein sequence data from the standard format to the new schema. We analyze four different methods of transformation and evaluate those four different methods. The results show that our proposed extended radix tree has the best performance regarding memory consumption and calculation time. Hence, the radix tree is proved to be a suitable data structure for the transformation of protein sequences into the indexed schema.
Supported by organization de.NBI and Bruker Daltonik GmbH.
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References
Deutsch, E.W.: File formats commonly used in mass spectrometry proteomics. Mol. Cell. Proteomics 11(12), 1612–1621 (2012)
Heyer, R., et al.: Metaproteomics of complex microbial communities in biogas plants. Microb. Technol. 8, 749–763 (2015)
Heyer, R., et al.: Challenges and perspectives of metaproteomic data analysis. J. Biotechnol. 261(Suppl. C), 24–36 (2017)
https://blast.ncbi.nlm.nih.gov/Blast.cgi?CMD=Web&PAGE_TYPE=BlastDocs&DOC_TYPE=BlastHelp:. Fasta format, November 2002
Leis, V., et al.: The adaptive radix tree: artful indexing for main-memory databases. In: IEEE International Conference on Data Engineering (ICDE 2013), pp. 38–49 (2013)
Millioni, R., et al.: Pros and cons of peptide isolectric focusing in shotgun proteomics. J. Chromatogr. A 1293, 1–9 (2013)
Petriz, B.A., et al.: Metaproteomics as a complementary approach to gut microbiota in health and disease. Front. Chem. 5, 4 (2017)
Shishibori, M., et al.: An efficient compression method for patricia tries. In: 1997 IEEE International Conference on Systems, Man, and Cybernetics. Computational Cybernetics and Simulation, vol. 1, pp. 415–420, October 1997
Zoun, R., et al.: Protein identification as a suitable application for fast data architecture. In: International Workshop on Biological Knowledge Discovery and Data Mining (BIOKDD-DEXA). IEEE, September 2018
Zoun, R., et al.: Msdatastream - connecting a bruker mass spectrometer to the internet. In: Datenbanksysteme für Business, Technologie und Web, March 2019
Acknowledgments
The authors sincerely thank Niya Zoun, Gabriel Cam-pero Durand, Marcus Pinnecke, Sebastian Krieter, Sven Helmer, Sven Brehmer and Andreas Meister for their support and advice. This work is partly funded by the BMBF (Fkz: 031L0103), the European Regional Development Fund (no.: 11.000sz00.00.0 17 114347 0), the DFG (grant no.: SA 465/50-1), by the German Federal Ministry of Food and Agriculture (grants no.: 22404015) and dedicated to the memory of Mikhail Zoun.
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Zoun, R. et al. (2019). Efficient Transformation of Protein Sequence Databases to Columnar Index Schema. In: Anderst-Kotsis, G., et al. Database and Expert Systems Applications. DEXA 2019. Communications in Computer and Information Science, vol 1062. Springer, Cham. https://doi.org/10.1007/978-3-030-27684-3_10
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DOI: https://doi.org/10.1007/978-3-030-27684-3_10
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