We present a methodology for biological data integration, aiming at building and analysing large functional networks which model complex genotype-phenotype associations. A functional network is a graph where nodes represent cellular components (e.g., genes, proteins, mRNA, etc.) and edges represent associations among such molecules. Different types of components may cohesist in the same network, and associations may be related to physical/biochemical interactions or functional/phenotipic relationships. Due to both the large amount of involved information and the computational complexity typical of the problems in this domain, the proposed framework is based on big data technologies (Spark and NoSQL databases).

Giallombardo C., Morfea S., Rombo S.E. (2018). An Integrative Framework for the Construction of Big Functional Networks. In H. Schmidt, D. Griol, H. Wang, J. Baumbach, H. Zheng, Z. Callejas, et al. (a cura di), Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine (pp. 2088-2093). 345 E 47TH ST, NEW YORK, NY 10017 USA : IEEE [10.1109/BIBM.2018.8621128].

An Integrative Framework for the Construction of Big Functional Networks

Rombo, SE
2018-01-01

Abstract

We present a methodology for biological data integration, aiming at building and analysing large functional networks which model complex genotype-phenotype associations. A functional network is a graph where nodes represent cellular components (e.g., genes, proteins, mRNA, etc.) and edges represent associations among such molecules. Different types of components may cohesist in the same network, and associations may be related to physical/biochemical interactions or functional/phenotipic relationships. Due to both the large amount of involved information and the computational complexity typical of the problems in this domain, the proposed framework is based on big data technologies (Spark and NoSQL databases).
2018
Settore INF/01 - Informatica
9781538654880
Giallombardo C., Morfea S., Rombo S.E. (2018). An Integrative Framework for the Construction of Big Functional Networks. In H. Schmidt, D. Griol, H. Wang, J. Baumbach, H. Zheng, Z. Callejas, et al. (a cura di), Proceedings - 2018 IEEE International Conference on Bioinformatics and Biomedicine (pp. 2088-2093). 345 E 47TH ST, NEW YORK, NY 10017 USA : IEEE [10.1109/BIBM.2018.8621128].
File in questo prodotto:
File Dimensione Formato  
08621128.pdf

Solo gestori archvio

Tipologia: Versione Editoriale
Dimensione 109.78 kB
Formato Adobe PDF
109.78 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/10447/387334
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus 1
  • ???jsp.display-item.citation.isi??? 0
social impact