Abstract
This paper presents a novel visual analytics method that incorporates knowledge from the analysis domain so that it can extract knowledge from complex genetic and clinical data and then visualizing them in a meaningful and interpretable way. The domain experts that are both contributors to formulating the requirements for the design of the system and the actual user of the system include microbiologists, biostatisticians, clinicians and computational biologists. A comprehensive prototype has been developed to support the visual analytics process. The system consists of multiple components enabling the complete analysis process, including data mining, interactive visualization, analytical views, gene comparison. A visual highlighting method is also implemented to support the decision making process. The paper demonstrates its effectiveness on a case study of childhood cancer patients.
| Original language | English |
|---|---|
| Title of host publication | Neural Information Processing: 18th International Conference, ICONIP 2011, Shanghai, China, November 13-17, 2011. Proceedings, Part I |
| Publisher | Springer |
| Pages | 113-120 |
| Number of pages | 8 |
| ISBN (Print) | 9783642249549 |
| DOIs | |
| Publication status | Published - 2011 |
| Event | ICONIP (Conference) - Duration: 1 Jan 2011 → … |
Publication series
| Name | |
|---|---|
| ISSN (Print) | 0302-9743 |
Conference
| Conference | ICONIP (Conference) |
|---|---|
| Period | 1/01/11 → … |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- data mining
- gene expression
- information visualisation
- lymphoblastic leukemia
- medical informatics
- microarray analysis
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