%0 Conference Proceedings
%T Mining Biological Data on the Cloud – A MapReduce Approach
%+ University of Patras
%+ Ionian University [Corfu]
%+ Technological Educational Institute of Western Greece [Patra] (TEI)
%A Ioannou, Zafeiria-Marina
%A Nodarakis, Nikolaos
%A Sioutas, Spyros
%A Tsakalidis, Athanasios
%A Tzimas, Giannis
%Z Part 2: MHDW Workshop
%< avec comité de lecture
%( IFIP Advances in Information and Communication Technology
%B 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI)
%C Rhodes, Greece
%Y Lazaros Iliadis
%Y Ilias Maglogiannis
%Y Harris Papadopoulos
%Y Spyros Sioutas
%Y Christos Makris
%I Springer
%3 Artificial Intelligence Applications and Innovations
%V AICT-437
%P 96-105
%8 2014-09-19
%D 2014
%R 10.1007/978-3-662-44722-2_11
%K Bioinformatics
%K Data mining
%K Text mining
%K Clustering
%K MapReduce
%K Hadoop
%Z Computer Science [cs]Conference papers
%X During last decades, bioinformatics has proven to be an emerging field of research leading to the development of a wide variety of applications. The primary goal of bioinformatics is to detect useful knowledge hidden under large volumes biological and biomedical data, gain a greater insight into their relationships and, therefore, enhance the discovery and the comprehension of biological processes. To achieve this, a great number of text mining techniques have been developed that efficiently manage and disclose meaningful patterns and correlations from biological and biomedical data repositories. However, as the volume of data grows rapidly these techniques cannot cope with the computational burden that is produced since they apply only in centralized environments. Consequently, a turn into distributed and parallel solutions is indispensable. In the context of this work, we propose an efficient and scalable solution, in the MapReduce framework, for mining and analyzing biological and biomedical data.
%G English
%Z TC 12
%Z WG 12.5
%2 https://inria.hal.science/hal-01391033/document
%2 https://inria.hal.science/hal-01391033/file/978-3-662-44722-2_11_Chapter.pdf
%L hal-01391033
%U https://inria.hal.science/hal-01391033
%~ IFIP
%~ IFIP-AICT
%~ IFIP-TC
%~ IFIP-WG
%~ IFIP-TC12
%~ IFIP-AIAI
%~ IFIP-WG12-5
%~ IFIP-AICT-437