This course for practicing and aspiring data scientists and statisticians. It is the fourth of a four-course sequence introducing the fundamentals of Bayesian statistics. It builds on the course Bayesian Statistics: From Concept to Data Analysis, Techniq
An, An informative approach on differen- tial abundance analysis for time-course metagenomic sequencing data, Bioinformatics 33 (2017), no. 9, 1286-1292.D. Luo, S. Ziebell, and L. An, An informative approach on differential abundance analysis for time-course metagenomic sequencing data, ...
Time course transcriptomics (RNA sequencing [RNA-seq] analysis), metabolomics, and glycan analyses were performed on the two processes. Statistical and functional analyses, including principal-component analysis (PCA), gene set enrichment analysis (GSEA) (Subramanian et al., 2005), time course gene...
A general analysis and comparison of side and time course expression trends.a. Distribution of genes in either the oral or physal regenerating sides according to their time course response pattern: always upregulated, always downregulated or other, having a more complex trend. Genes were considered...
Time-lapse transcriptome analysis of BoHV-1 using long-read sequencing In this work, we carried out a time-course analysis of the BoHV-1 transcriptome. In order to capture the most complete transcriptome dataset, we applied various experimental conditions (different cell types for virus propagation...
Time-series single-cell RNA sequencing (scRNAseq) can capture heterogeneity in cell states and transitions during dynamic biological processes, such as development and differentiation. Many trajectory inference methods have been developed to order cells by their progression through a dynamic process and ...
BEEM: Estimating Lotka-Volterra models from time-course microbiome sequencing data - GitHub - CSB5/BEEM: BEEM: Estimating Lotka-Volterra models from time-course microbiome sequencing data
Cluster analysis of gene expression data often involves multiple dis-tinct data sets, e. g., multiple time course measurements. Since existing clustering methods operate on a single matrix of expression data only, a common approach consists in aggregating all measurements into one data matrix. There...
Managing Teams, Data Analysis, Marketing Management, Accounting for Managers, Economics, Financial Management, Capstone Course-Strategic Management, International Business, Information Systems Management, five electives which can be focused on one of 15 areas of specialization such as: Sustainability, Sports...
Since cells make transitions over time, time series transcriptome data can be useful for predicting transitions of cell states as well. Liu et al. used Global nuclear Run-On sequencing (GRO-seq), RNA sequencing (RNA-seq), and histone-modification Chromatin ImmunoPrecipitation sequencing (ChIP-seq...