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iDREM: Interactive visualization of dynamic regulatory networks

The Dynamic Regulatory Events Miner (DREM) software reconstructs dynamic regulatory networks by integrating static protein-DNA interaction data with time series gene expression data. In recent years, several additional types of high-throughput time series data have been profiled when studying biolog...

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Detalles Bibliográficos
Autores principales: Ding, Jun, Hagood, James S., Ambalavanan, Namasivayam, Kaminski, Naftali, Bar-Joseph, Ziv
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5868853/
https://www.ncbi.nlm.nih.gov/pubmed/29538379
http://dx.doi.org/10.1371/journal.pcbi.1006019
Descripción
Sumario:The Dynamic Regulatory Events Miner (DREM) software reconstructs dynamic regulatory networks by integrating static protein-DNA interaction data with time series gene expression data. In recent years, several additional types of high-throughput time series data have been profiled when studying biological processes including time series miRNA expression, proteomics, epigenomics and single cell RNA-Seq. Combining all available time series and static datasets in a unified model remains an important challenge and goal. To address this challenge we have developed a new version of DREM termed interactive DREM (iDREM). iDREM provides support for all data types mentioned above and combines them with existing interaction data to reconstruct networks that can lead to novel hypotheses on the function and timing of regulators. Users can interactively visualize and query the resulting model. We showcase the functionality of the new tool by applying it to microglia developmental data from multiple labs.