IEEEVAST 2010 - PDF Preprint Papers

IEEEVAST 2010

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IEEEVAST
2010

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GeneTracer: Gene sequence analysis of disease mutations VAST 2010 mini challenge 3 award: Excellent process explanation

1 years 5 days ago

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Our visual analytics tool GeneTracer, developed for the VAST 2010 genetic sequence mini challenge, visualizes gene sequences of current outbreaks and native sequences along with d...

Hanseung Lee, Jaegul Choo, Carsten Görg, Jaee...

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Id	Views	Title	Status
1	55	GeneTracer: Gene sequence analysis of disease mutations VAST 2010 mini challenge 3 award: Excellent process explanation	claim
2	55	Anomaly detection in GPS data based on visual analytics	claim
3	52	Flow-based scatterplots for sensitivity analysis	claim
4	50	Diamonds in the rough: Social media visual analytics for journalistic inquiry	claim
5	48	Helping users recall their reasoning process	claim
6	44	Click2Annotate: Automated Insight Externalization with rich semantics	claim
7	44	ALIDA: Using machine learning for intent discernment in visual analytics interfaces	claim
8	41	Finding and visualizing relevant subspaces for clustering high-dimensional astronomical data using connected morphological operators	claim
9	39	Visually representing geo-temporal differences	claim
10	38	A continuous analysis process between desktop and collaborative visual analytics environments	claim
11	38	Geo-historical context support for information foraging and sensemaking: Conceptual model, implementation, and assessment	claim
12	37	Interactive querying of temporal data using a comic strip metaphor	claim
13	35	An exploratory study of co-located collaborative visual analytics around a tabletop display	claim
14	34	Interactive visual analysis of multiobjective optimizations	claim
15	32	NetClinic: Interactive visualization to enhance automated fault diagnosis in enterprise networks	claim
16	32	Improving the visual analysis of high-dimensional datasets using quality measures	claim
17	28	DimStiller: Workflows for dimensional analysis and reduction	claim
18	27	Understanding text corpora with multiple facets	claim
19	27	A visual analytics approach to model learning	claim
20	26	Comparing different levels of interaction constraints for deriving visual problem isomorphs	claim

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