@inproceedings{holzhueter2010,
  author = {Holzh{\"u}ter, Clemens and Hadlak, Steffen and Schumann, Heidrun},
  title = {Multi-Level Visualization for the Exploration of Temporal Trends in Simulation Data (Poster)},
  year = {2010},
  abstract = {Modeling and simulation in System Biology generates huge volumes of data. Usually hierarchical clustering is applied to allow for a multi-level visualization, and in this way for a visual exploration of such data sets at multiple levels of granularity. Different distance measures can be used to define the cluster hierarchy, but in any case the distance values are estimated based on the data values, rather than on sets of values representing, e.g. temporal trends. This poster  presents a new approach for defining and visualizing the cluster hierarchy. For this purpose, we introduce a similarity measure to cluster elements by their temporal trends. Our visualization approach shows both; the hierarchy and the clusters represented by characteristic data values and their quality over time. This allows for effectively exploring  different clusters and data values as well as to identify interesting data and trends.},
  address = {Baltimore, Maryland, USA},
  booktitle = {Winter Simulation Conference},
}