Visual Analytics for Comparing Multiple Clustering Results of Bioinformatics Data

[1]  D. Botstein,et al.  DNA microarray analysis of gene expression in response to physiological and genetic changes that affect tryptophan metabolism in Escherichia coli. , 2000, Proceedings of the National Academy of Sciences of the United States of America.

[2]  M. Shahriar Hossain,et al.  Scatter/Gather Clustering: Flexibly Incorporating User Feedback to Steer Clustering Results , 2012, IEEE Transactions on Visualization and Computer Graphics.

[3]  D. Botstein,et al.  Cluster analysis and display of genome-wide expression patterns. , 1998, Proceedings of the National Academy of Sciences of the United States of America.

[4]  Jinwook Seo,et al.  XCluSim: a visual analytics tool for interactively comparing multiple clustering results of bioinformatics data , 2015, BMC Bioinformatics.

[5]  Georges G. Grinstein,et al.  Visually comparing multiple partitions of data with applications to clustering , 2009, Electronic Imaging.

[6]  Doris Dransch,et al.  Visual Analytics for Comparison of Ocean Model Output with Reference Data: Detecting and Analyzing Geophysical Processes Using Clustering Ensembles , 2014, IEEE Transactions on Visualization and Computer Graphics.

[7]  Edwin de Jonge,et al.  Tree Colors: Color Schemes for Tree-Structured Data , 2014, IEEE Transactions on Visualization and Computer Graphics.

[8]  Heike Hofmann,et al.  Common Angle Plots as Perception-True Visualizations of Categorical Associations , 2013, IEEE Transactions on Visualization and Computer Graphics.

[9]  Hans-Peter Kriegel,et al.  OPTICS: ordering points to identify the clustering structure , 1999, SIGMOD '99.

[10]  Dieter Schmalstieg,et al.  VisBricks: Multiform Visualization of Large, Inhomogeneous Data , 2011, IEEE Transactions on Visualization and Computer Graphics.

[11]  Antony Unwin,et al.  Comparing Clusterings Using Bertin's Idea , 2012, IEEE Transactions on Visualization and Computer Graphics.

[12]  P. Rousseeuw Silhouettes: a graphical aid to the interpretation and validation of cluster analysis , 1987 .

[13]  Christian Posse,et al.  Diverse information integration and visualization , 2006, Electronic Imaging.

[14]  Ben Shneiderman,et al.  The eyes have it: a task by data type taxonomy for information visualizations , 1996, Proceedings 1996 IEEE Symposium on Visual Languages.

[15]  Georges G. Grinstein,et al.  Heat Map Visualizations Allow Comparison of Multiple Clustering Results and Evaluation of Dataset Quality: Application to Microarray Data , 2007, 2007 11th International Conference Information Visualization (IV '07).

[16]  Teuvo Kohonen,et al.  The self-organizing map , 1990 .

[17]  Ben Shneiderman,et al.  Interactively Exploring Hierarchical Clustering Results , 2002, Computer.

[18]  Dieter Schmalstieg,et al.  Caleydo: Design and evaluation of a visual analysis framework for gene expression data in its biological context , 2010, 2010 IEEE Pacific Visualization Symposium (PacificVis).

[19]  Chao Wang,et al.  iGPSe: A visual analytic system for integrative genomic based cancer patient stratification , 2014, BMC Bioinformatics.

[20]  Eser Kandogan,et al.  Just-in-time annotation of clusters, outliers, and trends in point-based data visualizations , 2012, 2012 IEEE Conference on Visual Analytics Science and Technology (VAST).

[21]  Dieter Schmalstieg,et al.  Comparative Analysis of Multidimensional, Quantitative Data , 2010, IEEE Transactions on Visualization and Computer Graphics.

[22]  Dino Pedreschi,et al.  Interactive visual clustering of large collections of trajectories , 2009, 2009 IEEE Symposium on Visual Analytics Science and Technology.

[23]  C. J. van Rijsbergen,et al.  FOUNDATION OF EVALUATION , 1974 .

[24]  Dieter Schmalstieg,et al.  StratomeX: Visual Analysis of Large‐Scale Heterogeneous Genomics Data for Cancer Subtype Characterization , 2012, Comput. Graph. Forum.

[25]  Ian H. Witten,et al.  The WEKA data mining software: an update , 2009, SKDD.

[26]  M. Sheelagh T. Carpendale,et al.  Bubble Sets: Revealing Set Relations with Isocontours over Existing Visualizations , 2009, IEEE Transactions on Visualization and Computer Graphics.

[27]  Yong-Joon Cho,et al.  A defect in iron uptake enhances the susceptibility of Cryptococcus neoformans to azole antifungal drugs. , 2012, Fungal genetics and biology : FG & B.

[28]  R. Kosara,et al.  Parallel sets: visual analysis of categorical data , 2005, IEEE Symposium on Information Visualization, 2005. INFOVIS 2005..