Titlebook: Statistical Modeling in Biomedical Research; Contemporary Topics Yichuan Zhao,Ding-Geng (Din) Chen Book 2020 Springer Nature Switzerland A

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Classification of EEG Motion Artifact Signals Using Spatial ICAd of computational neuroscience. In this paper, we proposed a novel procedure which reduce dimension by applying spatial Independent Component Analysis (SICA) on EEG motion artifact data and classify gait speed for a given subject by the projected EEG motion artifact signals. Whereas most applicatio

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Discrete Multiple Testing in Detecting Differential Methylation Using Sequencing Dataisease processes, such as cancer. We will discuss the multiple testing issue in detecting differential methylation in next generation sequencing studies. The detection requires comparing DNA methylation levels at millions of genomic loci across different genomic samples and can be viewed as a large-

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Prediction of Functional Markers of Mass Cytometry Data via Deep Learning markers across hundreds and thousands of cells. These measurements can often be used to differentiate various cell types and there has been a rapid development of analytic approaches for achieving this. However, in spite of the fact that measurements are available on such a large number of cells, t

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Hierarchical Continuous Time Hidden Markov Model, with Application in Zero-Inflated Accelerometer Datial to use such data to inform medical decision making and public health policies. However, modeling such data is challenging as they are high-dimensional, heterogeneous, and subject to informative missingness, e.g., zero readings when the device is removed by the participant. We propose a flexible

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Improving Maize Trait through Modifying Combination of Genesple genes simultaneously for trait improvement, we developed a systematic computational method aiming at detecting complex traits associated with gene interactions using a combination of gene expression and trait data across a set of maize hybrids. This method represents changes of expression patter