Computer Science and Applied Mathematics

Seeing Patterns in Data
Bang Wong, Broad Institute

The unprecedented scale and resolution of data generated by the biomedical research community hold tremendous potential to inform our understanding of disease. The shear volume of information, however, poses significant analytical challenges. The interpretation of these data for insights depends on our ability to explore them for patterns and relationships. Data visualization is a tantalizing approach because well-designed graphical depictions of information can replace arduous cognitive assessment with simple perceptual inferences. But looking for patterns in a data set like the one generated by the Broad Institute's Library of Integrated Cellular Networks with 1.7 million columns and 20,000 rows is no trivial task.

The success of data visualization depends on the development of methods and techniques to transform information into visual forms for understanding. Many current tools in biology do not adequately contribute to this goal as their rudimentary approach to visualization yields graphics that are too simple to be useful or so complex that they become incomprehensible. Data for the most part have no natural form, we have to make choices about how they are displayed. Each decision can bring out certain kinds of patterns in data while hiding others. We currently rely heavily on our intuition, common sense and precedent in published material when we visually depict data. This is largely an unscientific process. A rational framework for creating effective visual displays of data will support efficient data exploration and build critical leads for subsequent computational and machine-driven approaches to data analysis.

Background Review Articles:

Bang Wong (2010) Points of view: Color coding, 573-573. In Nature Methods 7 (8).

Bang Wong (2010) Points of view: Design of data figures, 665-665. In Nature Methods 7 (9).

Noam Shoresh, Bang Wong (2012) Points of View: Data exploration, 5. In Nature Methods 9 (1).

Nils Gehlenborg, Bang Wong (2012) Points of View: Mapping quantitative data to colorloration, 5. In Nature Methods 9 (8).

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Computer Science and Applied Mathematics

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The Kavli Frontiers of Science symposium series is the National Academy of Science’s premiere activity for distinguished young scientists. Unlike meetings that focus on a narrow area of science, these meetings allow participants to explore innovative…


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The Kavli Frontiers of Science symposium series is the National Academy of Science’s premiere activity for distinguished young scientists. Unlike meetings that focus on a narrow area of science, these meetings allow participants to explore innovative research ideas across a wide variety of fields and to develop new networks that will serve them as they progress in their careers..

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