Tuesday, July 16, 2019

Tending the future of data analysis with MVApp

New app aims to improve the statistical analysis of large datasets in plant science and beyond.

The vast datasets generated by modern plant-science technologies require clever data-mining methods to extract useful information. Now, KAUST researchers have developed MVApp—an open-source, online statistics platform for conducting multivariate analyses of these intricate data.

The recent development of high-throughput phenotyping techniques has rapidly produced huge datasets on the characteristics of plants. These multivariate data hold crucial details about plant physiology: how a plant responds to different environments and how a plant’s growth patterns and potential yields change—all of which are valuable in developing sustainable agriculture and ensuring food security.

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Image: The Arabidobsis thaliana plants shown here are growing on a conveyor belt that is part of plant-screening phenotyping system.
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