Εξειδίκευση τύπου :	Άρθρο σε επιστημονικό περιοδικό
Τίτλος:	GRISSOM Platform: Enabling Distributed Processing and Management of Biological Data Through Fusion of Grid and Web Technologies
Δημιουργός/Συγγραφέας:	[EL] Χατζηιωάννου, Αριστοτέλης[EN] Chatziioannou, Aristotelis Kanaris, Ioannis Doukas, Charalampos Moulos, Panagiotis [EL] Κολίσης, Φραγκίσκος Ν.[EN] Kolisis, Fragiskos N.‏ Maglogiannis, Ilias
Εκδότης:	IEEE-inst Electrical Electronics Engineers Incorporated
Τόπος έκδοσης:	Piscataway
Ημερομηνία:	2011-01
Γλώσσα:	Αγγλικά
ISSN:	1089-7771
DOI:	10.1109/TITB.2010.2092784
Περίληψη:	Transcriptomic technologies have a critical impact in the revolutionary changes that reshape biological research. Through the recruitment of novel high-throughput instrumentation and advanced computational methodologies, an unprecedented wealth of quantitative data is produced. Microarray experiments are considered high-throughput, both in terms of data volumes (data intensive) and processing complexity (computationally intensive). In this paper, we present grids for in silico systems biology and medicine (GRISSOM), a web-based application that exploits GRID infrastructures for distributed data processing and management, of DNA microarrays (cDNA, Affymetrix, Illumina) through a generic, consistent, computational analysis framework. GRISSOM performs versatile annotation and integrative analysis tasks, through the use of third-party application programming interfaces, delivered as web services. In parallel, by conforming to service-oriented architectures, it can be encapsulated in other biomedical processing workflows, with the help of workflow enacting software, like Taverna Workbench, thus rendering access to its algorithms, transparent and generic. GRISSOM aims to set a generic paradigm of efficient metamining that promotes translational research in biomedicine, through the fusion of grid and semantic web computing technologies.
Τίτλος πηγής δημοσίευσης:	Ieee Transactions on Information Technology in Biomedicine
Τόμος/Κεφάλαιο:	15
Τεύχος:	1
Σελίδες:	83-92
Θεματική Κατηγορία:	[EL] Βιολογία (Γενικά)[EN] Biology (General) [EL] Ηλεκτρονικοί υπολογιστές. Επιστήμη των υπολογιστών[EN] Electronic computers. Computer science
Λέξεις-Κλειδιά:	Biological data mining distributed computing grid translational biomedical research web services Computer Science, Information Systems Computer Science, Interdisciplinary Applications Medical Informatics
Αξιολόγηση από ομότιμους (peer reviewed):	Ναι
Κάτοχος πνευματικών δικαιωμάτων:	© IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Ηλεκτρονική διεύθυνση περιοδικού (link) :	http://ieeexplore.ieee.org/servlet/opac?punumber=4233
ΙΒΦΧΒ: αρχειακή συλλογή:	Ινστιτούτο Βιολογικών Ερευνών και Βιοτεχνολογίας (ΙΒΕΒ) (έως 2012)
Εμφανίζεται στις συλλογές:	Ινστιτούτο Χημικής Βιολογίας - Επιστημονικό έργο