Improving gene network inference by comparing expression time-series across species, developmental stages or tissues.
Improving gene network inference by comparing expression time-series across species, developmental stages or tissues.
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DOI：
10.1142/s0219720004000892
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发表时间：
2004-12-01
影响因子：
1
通讯作者：
Sankoff, David
中科院分区：
文献类型：
--
作者：
Bourque, Guillaume;Sankoff, David
提出了一种基于时间序列数据的基因网络推理和修正方法。基因网络建模使用线性微分方程和广义逐步多元线性回归过程被用来恢复的相互作用系数。我们的系统是专为恢复基因的相互作用，同时在许多基因调控网络相关的树或更一般的图形。我们展示了这种比较框架如何促进网络的恢复，并提高推断的解决方案的质量。
We present a method for gene network inference and revision based on time-series data. Gene networks are modeled using linear differential equations and a generalized stepwise multiple linear regression procedure is used to recover the interaction coefficients. Our system is designed for the recovery of gene interactions concurrently in many gene regulatory networks related by a tree or a more general graph. We show how this comparative framework can facilitate the recovery of the networks and improve the quality of the solutions inferred.