Eliater: a Python package for estimating outcomes of perturbations in biomolecular networks
Sara Mohammad-Taheri, Pruthvi Prakash Navada, Charles Tapley Hoyt, Jeremy Zucker, Karen Sachs, Benjamin M Gyori, Olga Vitek
TL;DR
Eliater is a Python tool that estimates how changing one molecule affects another in a biological network.
Contribution
Eliater introduces a novel Python package for quantifying perturbation effects in biomolecular networks.
Findings
Eliater estimates quantitative effects of molecular perturbations using observational data and network structures.
The package was demonstrated on Escherichia coli transcriptional regulatory networks.
Eliater is open source with documentation and case studies available.
Abstract
We introduce Eliater, a Python package for estimating the effect of perturbation of an upstream molecule on a downstream molecule in a biomolecular network. The estimation takes as input a biomolecular network, observational biomolecular data, and a perturbation of interest, and outputs an estimated quantitative effect of the perturbation. We showcase the functionalities of Eliater in a case study of Escherichia coli transcriptional regulatory network. The code, the documentation, and several case studies are available open source at https://github.com/y0-causal-inference/eliater.
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Taxonomy
TopicsBioinformatics and Genomic Networks · Gene Regulatory Network Analysis · Microbial Metabolic Engineering and Bioproduction