Mining Biological Data on the Cloud – A MapReduce Approach

Abstract : 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.
Type de document :
Communication dans un congrès
Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos; Spyros Sioutas; Christos Makris. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-437, pp.96-105, 2014, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-662-44722-2_11〉
Liste complète des métadonnées

Littérature citée [22 références]  Voir  Masquer  Télécharger

https://hal.inria.fr/hal-01391033
Contributeur : Hal Ifip <>
Soumis le : mercredi 2 novembre 2016 - 17:14:05
Dernière modification le : mardi 26 décembre 2017 - 16:38:01
Document(s) archivé(s) le : vendredi 3 février 2017 - 16:04:02

Fichier

978-3-662-44722-2_11_Chapter.p...
Fichiers produits par l'(les) auteur(s)

Licence


Distributed under a Creative Commons Paternité 4.0 International License

Identifiants

Citation

Zafeiria-Marina Ioannou, Nikolaos Nodarakis, Spyros Sioutas, Athanasios Tsakalidis, Giannis Tzimas. Mining Biological Data on the Cloud – A MapReduce Approach. Lazaros Iliadis; Ilias Maglogiannis; Harris Papadopoulos; Spyros Sioutas; Christos Makris. 10th IFIP International Conference on Artificial Intelligence Applications and Innovations (AIAI), Sep 2014, Rhodes, Greece. Springer, IFIP Advances in Information and Communication Technology, AICT-437, pp.96-105, 2014, Artificial Intelligence Applications and Innovations. 〈10.1007/978-3-662-44722-2_11〉. 〈hal-01391033〉

Partager

Métriques

Consultations de la notice

255

Téléchargements de fichiers

36