iDREM: Interactive visualization of dynamic regulatory networks

被引:27
作者
Ding, Jun [1 ]
Hagood, James S. [2 ,3 ]
Ambalavanan, Namasivayam [4 ]
Kaminski, Naftali [5 ]
Bar-Joseph, Ziv [1 ]
机构
[1] Carnegie Mellon Univ, Sch Comp Sci, Computat Biol Dept, Pittsburgh, PA 15213 USA
[2] Univ Calif San Diego, Dept Pediat, Div Resp Med, La Jolla, CA 92093 USA
[3] Rady Childrens Hosp, La Jolla, CA USA
[4] Univ Alabama Birmingham, Dept Pediat, Div Neonatol, Birmingham, AL USA
[5] Yale Sch Med, Sect Pulm Crit Care & Sleep Med, New Haven, CT USA
基金
美国国家科学基金会; 美国国家卫生研究院;
关键词
CELL RNA-SEQ; BRAIN-DEVELOPMENT; EXPRESSION; TRANSCRIPTOME; POPULATION; PROTEOME; SYSTEM; GENES;
D O I
10.1371/journal.pcbi.1006019
中图分类号
Q5 [生物化学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
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页数:10
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