Bayesian meta-analysis for identifying periodically expressed genes in fission yeast cell cycle

The effort to identify genes with periodic expression during the cell cycle from genome-wide microarray time series data has been ongoing for a decade. However, the lack of rigorous modeling of periodic expression as well as the lack of a comprehensive model for integrating information across genes and experiments has impaired the effort for the accurate identification of periodically expressed genes. To address the problem, we introduce a Bayesian model to integrate multiple independent microarray data sets from three recent genome-wide cell cycle studies on fission yeast. A hierarchical model was used for data integration. In order to facilitate an efficient Monte Carlo sampling from the joint posterior distribution, we develop a novel Metropolis--Hastings group move. A surprising finding from our integrated analysis is that more than 40% of the genes in fission yeast are significantly periodically expressed, greatly enhancing the reported 10--15% of the genes in the current literature. It calls for a reconsideration of the periodically expressed gene detection problem.Comment: Published in at http://dx.doi.org/10.1214/09-AOAS300 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org

The implementation of a disambiguation marching cubes algorithm

This thesis first systematically analyzes a classic surface generation algorithm, the marching cubes algorithm, in computer volume visualization, with emphasis on the mathematical background and the ambiguity problem of the algorithm. A simple and elegant disambiguation algorithm is then described and implemented. Finally, generated data from mathematical functions and real world data from scientific experiment are used to test the original marching cubes algorithm and the disambiguation algorithm

The EM Algorithm and the Rise of Computational Biology

In the past decade computational biology has grown from a cottage industry with a handful of researchers to an attractive interdisciplinary field, catching the attention and imagination of many quantitatively-minded scientists. Of interest to us is the key role played by the EM algorithm during this transformation. We survey the use of the EM algorithm in a few important computational biology problems surrounding the "central dogma"; of molecular biology: from DNA to RNA and then to proteins. Topics of this article include sequence motif discovery, protein sequence alignment, population genetics, evolutionary models and mRNA expression microarray data analysis.Comment: Published in at http://dx.doi.org/10.1214/09-STS312 the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org

Hamilton-Jacobi equations in metric spaces

These are lecture notes for our minicourse at OIST Summer Graduate School "Analysis and Partial Differential Equations" on June 12-17, 2023. We give an overview and collect a few important results concerning the well-posedness of Hamilton-Jacobi equations in metric spaces, especially several recently proposed notions of metric viscosity solutions to the eikonal equation. Basic knowledge about metric spaces and a review of viscosity solution theory in the Euclidean spaces are also presented.Comment: arXiv admin note: text overlap with arXiv:2005.1340

Self-assessment of Consecutive Interpreting by MTI Interpreting Students

Assessing the quality of interpreting practice and conducting targeted training is the key to improving interpreting ability of MTI student interpreters. By reviewing literature on interpreting assessment and self-assessment, the research has decided the parameters for self-assessment of consecutive interpreting practice, developed a self-assessment form and conducted self-assessment of MTI interpreting students for fifteen weeks. Research results show that students have developed awareness of autonomous quality monitoring and improved their overall interpreting ability