2011
DOI: 10.1186/1471-2105-12-304
|View full text |Cite
|
Sign up to set email alerts
|

Applications of the pipeline environment for visual informatics and genomics computations

Abstract: BackgroundContemporary informatics and genomics research require efficient, flexible and robust management of large heterogeneous data, advanced computational tools, powerful visualization, reliable hardware infrastructure, interoperability of computational resources, and detailed data and analysis-protocol provenance. The Pipeline is a client-server distributed computational environment that facilitates the visual graphical construction, execution, monitoring, validation and dissemination of advanced data ana… Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
2
1
1
1

Citation Types

0
39
0

Year Published

2012
2012
2018
2018

Publication Types

Select...
8
1
1

Relationship

6
4

Authors

Journals

citations
Cited by 32 publications
(39 citation statements)
references
References 42 publications
0
39
0
Order By: Relevance
“…To manage the raw and derived data, processing protocols and provenance we employed the LONI Pipeline [28, 38]. The Pipeline is a graphical workflow environment facilitating the collaborative design, execution, validation, visualization, modification and sharing of complex heterogeneous computational protocols.…”
Section: Methodsmentioning
confidence: 99%
“…To manage the raw and derived data, processing protocols and provenance we employed the LONI Pipeline [28, 38]. The Pipeline is a graphical workflow environment facilitating the collaborative design, execution, validation, visualization, modification and sharing of complex heterogeneous computational protocols.…”
Section: Methodsmentioning
confidence: 99%
“…The LONI Pipeline could be used to design, execute, validate, and deliver complex heterogeneous computational protocols. [32], [47]- [49] C. Feature Extraction Thus, through feature extraction it is possible to retrieve important data that can assist the characterization of a pathology. Feature extraction methodologies analyze objects or images to extract the most prominent features that are representative of the various classes of objects.…”
Section: B Region Of Interest / Segmentationmentioning
confidence: 99%
“…We applied network analysis to obtain new insights about large-scale regional connectivity and to compare morphological brain architectures and network properties between groups of IBS and HC subjects. To assist in our large-scale analyses we employed the Laboratory of Neuro Imaging (LONI) pipeline [39; 41; 136], a graphical workflow environment which allows users to describe executable tools in a graphical user interface and create processing modules as nodes in a graph representing the complete computational protocol [40; 42]. We provide evidence for both regional alterations in GM volume, as well as differences in regional properties of large scale structural brain networks in IBS compared to HCs.…”
Section: 10 Introductionmentioning
confidence: 99%