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Gene mapping is a statistical method used to localize human disease genes to particular regions of the human genome. When performing such analysis, a genetic likelihood space is generated and sampled, which results in a multidimensional scalar field. Researchers are interested in exploring this likelihood space through the use of visualization. Previous efforts at visualizing this space, though, were...
This paper describes an interactive data exploration system for molecular and clinical data in the field of personalized medicine. It addresses the essential but to date unsolved problem of how to identify connections between genetic variants and their corresponding diseases or the response to certain drugs and treatments, respectively. It is therefore necessary to connect genetic with clinical data...
For the critical task of gene module discovery in genomic research, we present a model-based hierarchical data clustering and visualization algorithm, visual statistical data analyzer (VISDA), which effectively exploits human-data interaction to improve the clustering outcome. Guided by a diagnostic tree, we apply VISDA to a muscular dystrophy dataset that contains a number of different phenotypic...
For the critical task of gene module discovery in genomic research, we present a model-based hierarchical data clustering and visualization algorithm, visual statistical data analyzer (VISDA), which effectively exploits human-data interaction to improve the clustering outcome. Guided by a diagnostic tree, we apply VISDA to a muscular dystrophy dataset that contains a number of different phenotypic...
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