Abstract Summary scFates provides an extensive toolset for the analysis of dynamic
trajectories comprising tree learning, feature association testing, branch differential …

Motivation: Microarray experiments are now routinely used to collect large-scale time series
data, for example to monitor gene expression during the cell cycle. Statistical analysis of this …

Microarray analysis from a yeast continuous synchrony culture system shows a genomewide
oscillation in transcription. Maximums in transcript levels occur at three nearly equally …

Motivation: Cellular processes cause changes over time. Observing and measuring those
changes over time allows insights into the how and why of regulation. The experimental …

Cell cycle progression is both regulated and accompanied by periodic changes in the
expression levels of a large number of genes. To investigate cell cycle-regulated …

The finding of a genome‐wide oscillation in transcription that gates cells into S phase and
coordinates mitochondrial and metabolic functions has altered our understanding of how the …

Motivation: Accurate time series for biological processes are difficult to estimate due to
problems of synchronization, temporal sampling and rate heterogeneity. Methods are …

The advent of single cell transcriptome analysis has permitted the discovery of cell-to-cell
variation in transcriptome expression of even presumptively identical cells. We hypothesize …

Measuring gene expression over time can provide important insights into basic cellular
processes. Identifying groups of genes with similar expression time-courses is a crucial first …

One of the main problems associated with high dimensional multimodal real life data sets is
how to extract relevant and significant features. In this regard, a fast and robust feature …