Name
Abstract | ||
|---|---|---|
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. |
Year | DOI | Venue |
|---|---|---|
2018 | 10.1371/journal.pcbi.1006019 | PLOS COMPUTATIONAL BIOLOGY |
Field | DocType | Volume |
Data mining,Time series,Data visualization,Biology,Software,Data type,Interactive visualization,Gene regulatory network,Genetics,Unified Model | Journal | 14 |
Issue | Citations | PageRank |
3 | 0 | 0.34 |
References | Authors | |
7 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jun Ding | 1 | 14 | 3.58 |
| James S. Hagood | 2 | 0 | 0.34 |
| Namasivayam Ambalavanan | 3 | 0 | 0.68 |
| Naftali Kaminski | 4 | 111 | 7.54 |
| Ziv Bar-Joseph | 5 | 1207 | 112.00 |