A Web-based and Grid-enabled dChip version for the analysis of large sets of gene expression data
2008
Web-based dChip Software for Analyzing Gene Expression Data
Sample size: 1000
publication
Evidence: moderate
Author Information
Author(s): Corradi Luca, Fato Marco, Porro Ivan, Scaglione Silvia, Torterolo Livia
Primary Institution: University of Genova
Hypothesis
Can dChip software be modified to analyze large datasets of gene expression data on Grid infrastructures?
Conclusion
A Grid-enabled software application for analyzing large microarray datasets has been developed and validated, showing good scalability results.
Supporting Evidence
- The software allows analysis of large datasets without hardware constraints.
- Validation tests showed consistent results across different dChip versions.
- Grid technologies enable access to distributed data and computational resources.
Takeaway
Researchers can now analyze large sets of gene data using a web-based tool without needing powerful computers.
Methodology
The dChip software was modified for execution on cluster and Grid environments, using parallelization strategies for analysis.
Limitations
The performance on Grid environments was slower compared to cluster environments.
Digital Object Identifier (DOI)
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