Title
Visexpress: Visual Exploration Of Differential Gene Expression Data
Abstract
Biologists are keen to understand how processes in cells react to environmental changes. Differential gene expression analysis allows biologists to explore functions of genes with data generated from different environments. However, these data and analysis lead to unique challenges since tasks are ill-defined, require implicit domain knowledge, comprise large volumes of data, and are, therefore, of explanatory nature. To investigate a scalable visualization-based solution, we conducted a design study with three biologists specialized in differential gene expression analysis. We stress our contributions in three aspects: first, we characterize the problem domain for exploring differential gene expression data and derive task abstractions and design requirements. Second, we investigate the design space and present an interactive visualization system, called VisExpress. Third, we evaluate the usefulness of VisExpress via a Pair Analytics study with real users and real data and report on insights that were gained by our experts with VisExpress.
Year
DOI
Venue
2017
10.1177/1473871615612883
INFORMATION VISUALIZATION
Keywords
Field
DocType
Information visualization, design study, bioinformatics visualization, interactive visual exploration, biological data, expression data, gene expression profiling, differential gene expression
Biological data,Data mining,Problem domain,Computer science,Artificial intelligence,Analytics,Computer vision,Domain knowledge,Information visualization,Visualization,Interactive visualization,Machine learning,Gene expression profiling
Journal
Volume
Issue
ISSN
16
1
1473-8716
Citations 
PageRank 
References 
1
0.35
27
Authors
9
Name
Order
Citations
PageRank
Svenja Simon1281.92
Sebastian Mittelstädt2363.64
Bum chul Kwon327816.46
Andreas Stoffel422911.66
richard landstorfer510.35
Klaus Neuhaus6181.72
anna muhlig710.35
siegfried scherer810.35
Daniel A. Keim977041141.60