MLCut: exploring multi-level cuts in dendrograms for biological data
Conference Proceeding
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...
Hierarchical Clustering with Multiple-Height Branch-Cut Applied to Short Time-Series Gene Expression Data
Conference Proceeding
Vogogias, A., Kennedy, J., & Archambault, D. (2016)
Hierarchical Clustering with Multiple-Height Branch-Cut Applied to Short Time-Series Gene Expression Data. In T. Isenberg, & F. Sadlo (Eds.), EuroVis 2016 - Posters. , (1-3). https://doi.org/10.2312/eurp.20161127
Rigid adherence to pre-specified thresholds and static graphical representations can lead to incorrect decisions on merging of clusters. As an alternative to existing automate...