SCENERY: A web-based application for network reconstruction and visualization of cytometry data

Giorgos Athineou, Giorgos Papoutsoglou, Sofia Triantafillou, Ioannis Basdekis, Vincenzo Lagani, Ioannis Tsamardinos

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Scopus citations

Abstract

Cytometry techniques allow to quantify morphological characteristics and protein abundances at a single-cell level. Data collected with these techniques can be used for addressing the fascinating, yet challenging problem of reconstructing the network of protein interactions forming signaling pathways and governing cell biological mechanisms. Network reconstruction is an established and well studied problem in the machine learning and data mining fields, with several algorithms already available. In this paper, we present the first web-oriented application, SCENERY, that allows scientists to rapidly apply state-of-the-art network-reconstruction methods on cytometry data. SCENERY comes with an easy-to-use user interface, a modular architecture, and advanced visualization functions. The functionalities of the application are illustrated on data from a publicly available immunology experiment.
Original languageEnglish (US)
Title of host publicationAdvances in Intelligent Systems and Computing
PublisherSpringer Verlagservice@springer.de
Pages203-211
Number of pages9
ISBN (Print)9783319401256
DOIs
StatePublished - Jan 1 2016
Externally publishedYes

Bibliographical note

Generated from Scopus record by KAUST IRTS on 2023-09-23

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