Mining Biological Data on the Cloud – A MapReduce Approach - Inria - Institut national de recherche en sciences et technologies du numérique Access content directly
Conference Papers Year : 2014

Mining Biological Data on the Cloud – A MapReduce Approach

Zafeiria-Marina Ioannou
  • Function : Author
  • PersonId : 992339
Nikolaos Nodarakis
  • Function : Author
  • PersonId : 992340
Spyros Sioutas
  • Function : Author
  • PersonId : 992341
Athanasios Tsakalidis
  • Function : Author
  • PersonId : 992342


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.
Fichier principal
Vignette du fichier
978-3-662-44722-2_11_Chapter.pdf (242.74 Ko) Télécharger le fichier
Origin : Files produced by the author(s)

Dates and versions

hal-01391033 , version 1 (02-11-2016)





Zafeiria-Marina Ioannou, Nikolaos Nodarakis, Spyros Sioutas, Athanasios Tsakalidis, Giannis Tzimas. Mining Biological Data on the Cloud – A MapReduce Approach. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. pp.96-105, ⟨10.1007/978-3-662-44722-2_11⟩. ⟨hal-01391033⟩
162 View
83 Download



Gmail Facebook Twitter LinkedIn More