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, ...
Conclusions: The proposed method is powerful and efficient to detect biologically relevant DE genes and gene sets in time course RNA-Seq data. Keywords: Differentially expressed gene, Gene set enrichment, Analysis of variance, Smoothing spline, Penalized likelihood Background RNA-sequencing (RNA-Seq)...
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
In this course you learn to build, refine, extrapolate, and, in some cases, interpret models designed for a single, sequential series. There are three modeling approaches presented. The traditional, Box-Jenkins approach for modeling time series is covere
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
A real-time data analytics process will lean on the quality of an organization’s overall data management practices. Enterprise data management software should include the ability to scale quickly, integrate data from many sources, ensure data quality and strong governance, and, of course, prioritize...
Here we used a deep 16S amplicon sequencing approach to profile the bacterial community in eutrophic Lake Champlain over time, to characterise the composition and repeatability of cyanobacterial blooms, and to determine the potential for blooms to be predicted based on time course sequence data. Our...
Material for the course "Time series analysis with Python" coursesignal-processingrecurrent-neural-networksquantitative-financereservoir-computingarimachaos-theoryprophetkalman-filtertime-series-analysisfourier-transformtime-series-clusteringmoving-averagetime-series-classificationexponential-smoothingtime-series-forecasti...
In such networks, data flow transformations are passed via hidden layers in one direction where the output is influenced only with the current situation. However, these neural networks possess less memory and are not suitable for modeling data sequencing, and time dependencies in historical data. ...
Ilyonectria robusta causes rusty root rot, the most devastating chronic disease of ginseng. Here, we for the first time report the high-quality genome of the I. robusta strain CD-56. Time-course (36 h, 72 h, and 144 h) dual RNA-Seq analysis of t