GeneSPIDER - Generation and Simulation Package for Informative Data ExploRation
(English)Manuscript (preprint) (Other academic)
A range of tools are available to model, simulate and analyze gene regulatory networks (GRNs). However, these tools provide limited ability to control network topology, system dynamics, design of experiments, data properties, or noise characteristics. Independent control of these properties is the key to drawing conclusions on which inference method to use and what result to expect from it, as well as obtaining desired approximations of real biological systems. To draw conclusions on the relation between a network or data property and the performance of an inference method in simulations, system approximations with varying properties are needed. We present a Matlab package \gs for generation and analysis of networks and data in a dynamical systems framework with focus on the ability to vary properties. It supplies not only essential components that have been missing, but also wrappers to existing tools in common use. In particular, it contains tools for controlling and analyzing network topology (random, small-world, scale-free), stability of linear time-invariant systems, signal to noise ratio (SNR), and Interampatteness. It also contains methods for design of perturbation experiments, bootstrapping, analysis of linear dependence, sample selection, scaling of the SNR, and performance evaluation. GeneSPIDER offers control of network and data properties in simulations, together with tools to analyze these properties and draw conclusions on the quality of inferred GRNs. It can be fetched freely from the online =git= repository https://bitbucket.org/sonnhammergrni/genespider.
Bioinformatics and Systems Biology
Research subject Biochemistry towards Bioinformatics
IdentifiersURN: urn:nbn:se:su:diva-122146OAI: oai:DiVA.org:su-122146DiVA: diva2:865169