Abstract
The cancer and the cancer mortality may seem the sign of the present times. This leads hundreds of scientists to handle the issue of finding significant premises of cancer occurrence. In this paper a set of data mining tasks is defined that joins the observed genes mutation with the specific cancer type observation. Due to the high computational complexity of this kind of data a Hadoop ecosystem cluster was developed to perform the required calculations. The results may be satisfactory in the domains of distributed data storage (processing) and the genes mutation occurrence interpretation.
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Acknowledgements
This work was partially supported by Polish National Centre for Research and Development (NCBiR) within the programme Prevention and Treatment of Civilization Diseases—STRATEGMED III.
Grant No. STRATEGMED3/304586/5/NCBR/2017 (PersonALL). The work was carried out in part (especially the participation of the fifth author) within the statutory research project of the Institute of Informatics, BK-213/RAU2/2018.
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Bochenek, M. et al. (2018). The Use of Distributed Data Storage and Processing Systems in Bioinformatic Data Analysis. In: Kozielski, S., Mrozek, D., Kasprowski, P., Małysiak-Mrozek, B., Kostrzewa, D. (eds) Beyond Databases, Architectures and Structures. Facing the Challenges of Data Proliferation and Growing Variety. BDAS 2018. Communications in Computer and Information Science, vol 928. Springer, Cham. https://doi.org/10.1007/978-3-319-99987-6_2
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