FastMEDUSA: a parallelized tool to infer gene regulatory networks
FastMEDUSA: a parallelized tool to infer gene regulatory networks
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DOI：
10.1093/bioinformatics/btq275
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发表时间：
2010-07-15
期刊：
影响因子：
5.8
通讯作者：
Fine, Howard A.
中科院分区：
文献类型：
--
作者：
Bozdag, Serdar;Li, Aiguo;Fine, Howard A.
动机：为了有效地从基因表达和启动子序列数据中构建高等生物的基因调控网络，我们开发了FastMEDUSA。在这个调控网络建模工具Medusa的并行化版本中，在单个多核机器或集群上的用户定义数量的处理器之间共享表达和序列数据。我们的结果表明，FastMEDUSA可以更有效地利用计算资源。用Medusa确定智人脑瘤的调控网络需要12天，而FastMEDUSA使用100个处理器在6小时内就得到了同样的结果。
Motivation: In order to construct gene regulatory networks of higher organisms from gene expression and promoter sequence data efficiently, we developed FastMEDUSA. In this parallelized version of the regulatory network-modeling tool MEDUSA, expression and sequence data are shared among a user-defined number of processors on a single multi-core machine or cluster. Our results show that FastMEDUSA allows a more efficient utilization of computational resources. While the determination of a regulatory network of brain tumor in Homo sapiens takes 12 days with MEDUSA, FastMEDUSA obtained the same results in 6 h by utilizing 100 processors.