Name
Abstract | ||
|---|---|---|
In this article, we present an interactive prototype that aids the interpretation of large-scale gene expression data, showing how visualization techniques can be applied to support knowledge extraction from large datasets. The developed prototype was evaluated on a dataset of human embryonic stem cell-derived cardiomyocytes. The visualization approach presented here supports the analyst in finding genes with high similarity or dissimilarity across different experimental groups. By using an external overview in combination with filter windows, and various color scales for showing the degree of similarity, our interactive visual prototype is able to intuitively guide the exploration processes over the large amount of gene expression data. |
Year | DOI | Venue |
|---|---|---|
2016 | 10.1109/IV.2016.58 | 2016 20th International Conference Information Visualisation (IV) |
Keywords | DocType | ISSN |
gene expression data,similarity,visual analytics,decision-making | Conference | 1550-6037 |
ISBN | Citations | PageRank |
978-1-4673-8943-3 | 1 | 0.35 |
References | Authors | |
21 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Maria Riveiro | 1 | 133 | 18.64 |
| Mikael Lebram | 2 | 68 | 9.52 |
| Christian X. Andersson | 3 | 1 | 0.35 |
| Peter Sartipy | 4 | 1 | 0.35 |
| Jane Synnergren | 5 | 1 | 0.35 |