Computational Analysis of Post-Transcriptional Regulatory Mechanisms

Benchmarking selected computational gene network growing tools in context of virus-host interactions

Several available online tools provide network growing functions where an algorithm utilizing different data sources suggests additional genes/proteins that should connect an input gene set into functionally meaningful networks. Using the well-studied system of influenza host interactions, we compare the network growing function of two free tools GeneMANIA and STRING and the commercial IPA for their performance of recovering known influenza A virus host factors previously identified from siRNA screens.

type: 
Journal Paper
journal: 
Scientific Reports, 2017 Jul 19;7(1):5805. doi: 10.1038/s41598-017-06020-6
pubmed: 
28724991
Url: 
https://www.ncbi.nlm.nih.gov/pubmed/28724991
Impact Factor: 
4.259
Date of acceptance: 
2017-06-07

Transcriptome dynamics of the microRNA inhibition response

We report a high-resolution time series study of transcriptome dynamics following antimiR-mediated inhibition of miR-9 in a Hodgkin lymphoma cell-line—the first such dynamic study of the microRNA inhibition response—revealing both general and specific aspects of the physiological response. We show miR-9 inhibition inducing a multiphasic transcriptome response, with a direct target perturbation before 4 h, earlier than previously reported, amplified by a downstream peak at ∼32 h consistent with an indirect response due to secondary coherent regulation.

type: 
Journal Paper
journal: 
Nucleic Acids Research, 2015, 1, doi: 10.1093/nar/gkv603
Url: 
http://nar.oxfordjournals.org/content/early/2015/06/17/nar.gkv603.abstract
Impact Factor: 
8.808
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