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CSI: a nonparametric Bayesian approach to network inference from multiple perturbed time series gene expression data. (English) Zbl 1329.92007

Summary: Here we introduce the causal structure identification (CSI) package, a Gaussian process based approach to inferring gene regulatory networks (GRNs) from multiple time series data. The standard CSI approach infers a single GRN via joint learning from multiple time series datasets; the hierarchical approach (HCSI) infers a separate GRN for each dataset, albeit with the networks constrained to favor similar structures, allowing for the identification of context specific networks. The software is implemented in MATLAB and includes a graphical user interface (GUI) for user friendly inference. Finally the GUI can be connected to high performance computer clusters to facilitate analysis of large genomic datasets.

MSC:

92-04 Software, source code, etc. for problems pertaining to biology
62-04 Software, source code, etc. for problems pertaining to statistics
62G99 Nonparametric inference
60G15 Gaussian processes
92C42 Systems biology, networks
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References:

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