Visualization and Analysis of 3D Gene Expression Data
Recent methods for extracting precise measurements ofspatial gene expression patterns from three-dimensional (3D) image dataopens the way for new analysis of the complex gene regulatory networkscontrolling animal development. To support analysis of this novel andhighly complex data we developed PointCloudXplore (PCX), an integratedvisualization framework that supports dedicated multi-modal, physical andinformation visualization views along with algorithms to aid in analyzingthe relationships between gene expression levels. Using PCX, we helpedour science stakeholders to address many questions in 3D gene expressionresearch, e.g., to objectively define spatial pattern boundaries andtemporal profiles of genes and to analyze how mRNA patterns arecontrolled by their regulatory transcription factors.
- Research Organization:
- Ernest Orlando Lawrence Berkeley NationalLaboratory, Berkeley, CA (US)
- Sponsoring Organization:
- USDOE Director. Office of Science. Advanced ScientificComputing Research
- DOE Contract Number:
- AC02-05CH11231
- OSTI ID:
- 928239
- Report Number(s):
- LBNL--63658; BnR: KJ0101030
- Country of Publication:
- United States
- Language:
- English
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