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Fushing Hsieh

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Articles

Computationally unraveling genetic factors underlying morphological patterns of wheat’s root growth: a scientific data analysis approach

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By Chih-Wei Tung, Li-yu Daisy Liu, Fushing Hsieh, Shang-Chieh Lin, Hao-Chia Lo
| Nature Verified
Abstract A collection of 53 wheat varieties’ root-growth trajectories was clustered into seven distinct morphological growth patterns. Across more than 30K DNA variants, we used Categorical Exploratory Data Analysis (CEDA) to examine all 21 pairwise contrasts between these patterns. Short single- and multi-locus genotype combinations were evaluated by entropy reduction and a finite-sample reliability check based on alternative and null ensembles of contingency tables.
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Sensors | Free Full-Text | Livestock Informatics Toolkit: A Case Study in Visually Characterizing Complex Behavioral Patterns across Multiple Sensor Platforms, Using Novel Unsupervised Machine Learning and Information Theoretic Approaches

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By Fushing Hsieh, Pablo J. Pinedo, Catherine McVey, Diego Manriquez
| MDPI
All articles published by MDPI are made immediately available worldwide under an open access license. No special permission is required to reuse all or part of the article published by MDPI, including figures and tables. For articles published under an open access Creative Common CC BY license, any part of the article may be reused without permission provided that the original article is clearly cited.
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DCG++: A data-driven metric for geometric pattern recognition

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By of California Davis, Jiahui Guan, Fushing Hsieh, Patrice Koehl
| PLOS
Loading metrics Open Access Peer-reviewed Research Article Jiahui Guan, Fushing Hsieh, Patrice Koehl Jiahui Guan, Fushing Hsieh, Patrice Koehl Published: June 6, 2019 https://doi.org/10.1371/journal.pone.0217838 Figures Abstract Clustering large and complex data sets whose partitions may adopt arbitrary shapes remains a difficult challenge.
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