Projectome: Set up and testing of a High Performance Computational Infrastructure for processing and visualizing neuro-anatomical information obtained using confocal ultra-microscopy techniques
Ludovico
Silvestri1*,
Alessandro
Bria2,
Leonardo
Sacconi1,
Anna Letizia
Allegra Mascaro1,
Maria Chiara
Pettenati3,
Sanzio
Bassini4,
Carlo
Cavazzoni4,
Giovanni
Erbacci4,
Roberta
Turra4,
Giuseppe
Fiameni4,
Valeria
Ruggiero5,
Paolo
Frasconi6,
Simone
Marinai6,
Marco
Gori7,
Paolo
Nesi6,
Renato
Corradetti8,
Giulio
Iannello2 and
Francesco Saverio
Pavone9
-
1
LENS, Italy
-
2
UCBM, Italy
-
3
ICON, Italy
-
4
CINECA, Italy
-
5
UNIFE, Italy
-
6
DSI - UNIFI, Italy
-
7
DiSI - UNISI, Italy
-
8
Neuroscience - UNIFI, Italy
-
9
ICON, LENS, Italy
In Projectome we set up an IT infrastructure to share both neuroscience data as well as high performance computational applications. Data handled in Projectome are mouse brain images obtained using conf-u [1], a confocal ultra-microscopy technique in which selectively labeled neurons are imaged by light-sheet based microscopy [2][3] with micron-scale resolution. Data obtained from an experiment conducted on a mouse brain (1 cubic cm) might be of a range of 1 Terabyte, or more. Specific processes have been implemented in a Projectome Tooolkit in order to allow: 1) fully automated 3D Stitching capability starting from acquired raw data and 2) semi-automatic extraction of some morphological characteristics (eg. neurons localization) [1][4]. The implementation plan of the project consists of two phases: phase I, in which the core data management functions are set up and phase II in which the data mining, knowledge extraction and visualization features are implemented. Projectome is running the final part of phase I: both raw and processed data as well as elaboration algorithms are made available through a dedicated storage and computational infrastructure operated by CINECA, the largest Italian computing center [5]. Data sets originated from the European Laboratory of Non-linear Spectroscopy LENS [6] are transferred to CINECA using high performance protocol (i.e. GridFTP) and successively stored using iRODS data grid [7]. The setup of a Workflow Management System for the execution of Projectome Toolkit applications is being implemented using UNICORE [8]. [1] Silvestri, Bria, Sacconi, Iannello and Pavone, Confocal ultramicroscopy: micron-scale neuroanatomy of the entire mouse brain (2012). Submitted paper [2] Dodt et al., Ultramicroscopy: three-dimensional visualization of neuronal networks in the whole mouse brain, Nat Methods (2007) [3] Keller and Dodt, Light sheet microscopy of living or cleared specimens, Curr Opin Neurobiol (2011) – REVIEW [4] Bria, Silvestri, Sacconi, Pavone and Iannello, Stitching Terabyte-sized 3D images acquired in confocal ultramicrocopy, IEEE International Symposium on Biomedical Imaging (ISBI 2012), Barcelona, Spain, 2-5 May, 2012 [5] http://www.cineca.it/en [6] http://www.lens.unifi.it/ [7] iRODS (Integrated Rule-Oriented Data System) https://www.irods.org/ [8] UNICORE (Uniform Interface to Computing Resources) http://www.unicore.eu/
Keywords:
Neuroimaging
Conference:
5th INCF Congress of Neuroinformatics, Munich, Germany, 10 Sep - 12 Sep, 2012.
Presentation Type:
Poster
Topic:
Neuroinformatics
Citation:
Silvestri
L,
Bria
A,
Sacconi
L,
Allegra Mascaro
A,
Pettenati
M,
Bassini
S,
Cavazzoni
C,
Erbacci
G,
Turra
R,
Fiameni
G,
Ruggiero
V,
Frasconi
P,
Marinai
S,
Gori
M,
Nesi
P,
Corradetti
R,
Iannello
G and
Pavone
F
(2014). Projectome: Set up and testing of a High Performance Computational Infrastructure for processing and visualizing neuro-anatomical information obtained using confocal ultra-microscopy techniques.
Front. Neuroinform.
Conference Abstract:
5th INCF Congress of Neuroinformatics.
doi: 10.3389/conf.fninf.2014.08.00129
Copyright:
The abstracts in this collection have not been subject to any Frontiers peer review or checks, and are not endorsed by Frontiers.
They are made available through the Frontiers publishing platform as a service to conference organizers and presenters.
The copyright in the individual abstracts is owned by the author of each abstract or his/her employer unless otherwise stated.
Each abstract, as well as the collection of abstracts, are published under a Creative Commons CC-BY 4.0 (attribution) licence (https://creativecommons.org/licenses/by/4.0/) and may thus be reproduced, translated, adapted and be the subject of derivative works provided the authors and Frontiers are attributed.
For Frontiers’ terms and conditions please see https://www.frontiersin.org/legal/terms-and-conditions.
Received:
21 Mar 2013;
Published Online:
27 Feb 2014.
*
Correspondence:
Dr. Ludovico Silvestri, LENS, Sesto Fiorentino Firenze, Italy, silvestri@lens.unifi.it