Many important data in current biological science comprise hundreds, thousands or more individual results. These massive data require computational tools to navigate results and effectively interact with the content. Mobile device apps are an increasingly important tool in the everyday lives of scientists and non-scientists alike. These software present individuals with compact and efficient tools to interact with complex data at meetings or other locations remote from their main computing environment. We believe that apps will be important tools for biologists, geneticists and physicians to review content while participating in biomedical research or practicing medicine. We have developed a prototype app for displaying gene expression data using the iOS platform. To present the software engineering requirements, we review the model-view-controller schema for Apple's iOS. We apply this schema to a simple app for querying locally developed microarray gene expression data. The challenge of this application is to balance between storing content locally within the app versus obtaining it dynamically via a network connection. © The Author 2012. Published by Oxford University Press. All rights reserved.
CITATION STYLE
James, R. A., Rao, M. M., Chen, E. S., Goodell, M. A., & Shaw, C. A. (2012). The hematopoietic expression viewer: Expanding mobile apps as a scientific tool. Bioinformatics, 28(14), 1941–1942. https://doi.org/10.1093/bioinformatics/bts279
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