The analysis of gene expression from time series underpins many biological studies. Two basic forms of analysis recur for data of this type: removing inactive (quiet) genes from the study and determining which genes are differentially expressed. Often these analysis stages are applied disregarding the fact that the data is drawn from a time series.
Source text:
(Kalaitzis and Lawrence 2011) A simple approach to ranking differentially expressed gene expression time courses through Gaussian process regression. BMC Bioinformatics.
A software program specifically designed for the analysis of short time series…
A software program specifically designed for the analysis of short time series microarray gene expression data. STEM implements unique methods to cluster, compare, and visualize such data. STEM also…
A package specifically suited for the analysis of time-course gene expression…
A package specifically suited for the analysis of time-course gene expression data, which was developed originally for microarrays and hence was limited in its application to count data. Updated…
Package for assessing the statistical significance of periodic expression based…
Package for assessing the statistical significance of periodic expression based on Fourier analysis and comparison with data generated by different background models.
Captures single impulse-like progression patterns in high throughput time…
Captures single impulse-like progression patterns in high throughput time series datasets. ImpulseDE can be applied on any kind of high throughput gene expression data. It reports differentially…
Analyses sparse and heterogeneous time course data with high detection…
Analyses sparse and heterogeneous time course data with high detection sensitivity and transparency. TTCA is specifically designed for the analysis of perturbation responses. It combines different…
Package for noise-robust soft clustering of gene expression time-series data…
Package for noise-robust soft clustering of gene expression time-series data (including a graphical user interface).
A package for ranking differentially expressed gene expression time courses…
A package for ranking differentially expressed gene expression time courses through Gaussian process regression. gprege fits two GPs with the an RBF (+ noise diagonal) kernel on each profile. One GP…
Identifies gene clusters that exhibit distinctly similar or different gene…
Identifies gene clusters that exhibit distinctly similar or different gene expression patterns among the comparing sample conditions. TimesVector is a triclustering algorithm which is designed for…
Allows for capturing important features of the gene dynamic behaviour.…
Allows for capturing important features of the gene dynamic behaviour. SwitchFinder is a statistical method for the analysis of time-series data, in particular gene expression data, based on a…
A computational tool for analysing multiple gene expression time series data…
A computational tool for analysing multiple gene expression time series data sets for the same organism.
An integrated software platform for the analysis of microarray gene expression…
An integrated software platform for the analysis of microarray gene expression data. EXPANDER is designed to support all the stages of microarray data analysis, from raw data normalization to…
A filter-based feature selection method for temporal gene expression data based…
A filter-based feature selection method for temporal gene expression data based on maximum relevance and minimum redundancy criteria. TMRMR incorporates temporal information by combining relevance,…
Measures genomic features such as gene expression levels over time. DPGP is a…
Measures genomic features such as gene expression levels over time. DPGP is a statistical model for clustering time series data that identifies disjoint clusters of time series gene expression…
Treats the interaction strengths as random variables which are modulated by…
Treats the interaction strengths as random variables which are modulated by suitable priors. NETGEM is a tractable model rooted in Markov dynamics, for analyzing the dynamics of the interactions…
Implements a wavelet-based model for analyzing transcriptome data and extends…
Implements a wavelet-based model for analyzing transcriptome data and extends it towards more complex experimental designs. With waveTiling, the user is able to discover group-wise expressed regions,…
Provides an analytical framework to dissect such datasets and ultimately…
Provides an analytical framework to dissect such datasets and ultimately accelerate knowledge discovery through visualization and data-mining. MAPT is a user-friendly tool for both time-series and…
Detects dependencies between genes at different time delays in order to infer…
Detects dependencies between genes at different time delays in order to infer gene regulatory networks from time-series measurements starting from a well known algorithm based on information theory.…
Offers functions for data analysis and graphical displays for developmental…
Offers functions for data analysis and graphical displays for developmental microarray time course data.
Compares temporal gene expression patterns. NACEP compares the temporal…
Compares temporal gene expression patterns. NACEP compares the temporal patterns of a gene between two experimental conditions, taking into consideration all of the possible co-expression modules…
It was developed using an iterative software development cycle that involved a…
It was developed using an iterative software development cycle that involved a high level of user feedback and evaluation. MaTSE is an exploratory analysis tool that allows users to find unexpected…
Utilizes the proven and successful KEGG web-service to map numerical expression…
Utilizes the proven and successful KEGG web-service to map numerical expression onto biochemical pathways. PAICE is a rapid bioinformatics pathway visualization tool for KEGG-compatible accessions…
A package to identify differentially expressed genes in microarray time-course…
A package to identify differentially expressed genes in microarray time-course data. BETR explicitly uses the time-dependent structure of the data, employing an empirical Bayes procedure to stabilize…
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