Hosted by: Wei Xu

A number of challenges in studying biological systems have arisen over the last decades, related to the complexity of biological data. First, biological systems dynamically change in nature. Second, biological data can feature a broad range of scales. For example, brain activation data may range from the macroscale level to the microscale level. In addition, biological modeling involves multiple models and/or multiple simulation runs. Last but not least, a large number of biological problems contain both spatial and non-spatial features. For example, neuroscientists study brain networks by looking for correlations between brain structures and functional connections. This wealth of data, features, models, and potential hypotheses and experiments exceeds the analytical capabilities of machines. Visualization provides an effective way to help biologists understand, communicate, and gain insight into their biological data through visual analysis and exploration. I have contributed to a survey of visual integration techniques for spatial and non-spatial data in biology, summarized the domain data and tasks in dynamic biological systems analyses, created several innovative visual designs, and developed three visualization applications to those systems, performed in collaboration with domain experts.