Visual Analytics of Clinical and Genetic Datasets of Acute Lymphoblastic Leukaemia

Publisher:
Springer
Publication Type:
Conference Proceeding
Citation:
Lecture Notes in Computer Science (LNCS) 7062, 2011, pp. 113 - 120
Issue Date:
2011-01
Full metadata record
Files in This Item:
Filename Description Size
Thumbnail2011001178OK.pdf Published version12.07 MB
Adobe PDF
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.
Please use this identifier to cite or link to this item: