Visual Encodings for Networks with Multiple Edge Types
Vogogias, T., Archambault, D. W., Bach, B., & Kennedy, J. (2020)
Visual Encodings for Networks with Multiple Edge Types. In AVI '20: Proceedings of the International Conference on Advanced Visual Interfaces. https://doi.org/10.1145/3399715.3399827
This paper reports on a formal user study on visual encodings of networks with multiple edge types in adjacency matrices. Our tasks and conditions were inspired by real proble...
BayesPiles: Visualisation Support for Bayesian Network Structure Learning
Vogogias, A., Kennedy, J., Archambault, D., Bach, B., Smith, V. A., & Currant, H. (2018)
BayesPiles: Visualisation Support for Bayesian Network Structure Learning. ACM transactions on intelligent systems and technology, 10(1), 1-23. https://doi.org/10.1145/3230623
We address the problem of exploring, combining and comparing large collections of scored, directed networks for understanding inferred Bayesian networks used in biology. In th...
MLCut: exploring multi-level cuts in dendrograms for biological data
Vogogias, A., Kennedy, J., Archambault, D., Anne Smith, V., & Currant, H. (2016)
MLCut: exploring multi-level cuts in dendrograms for biological data. In C. Turkay, & T. Ruan Wan (Eds.), Computer Graphics and Visual Computing (CGVC)https://doi.org/10.2312/cgvc.20161288
Choosing a single similarity threshold for cutting dendrograms is not sufficient for performing hierarchical clustering analysis of heterogeneous data sets. In addition, alter...