Can ODE gene regulatory models neglect time lag or measurement scaling?
Publication in refereed journal

香港中文大學研究人員
替代計量分析
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其它資訊
摘要Motivation
Many ordinary differential equation (ODE) models have been introduced to replace linear regression models for inferring gene regulatory relationships from time-course gene expression data. But, since the observed data are usually not direct measurements of the gene products or there is an unknown time lag in gene regulation, it is problematic to directly apply traditional ODE models or linear regression models.

Results
We introduce a lagged ODE model to infer lagged gene regulatory relationships from time-course measurements, which are modeled as linear transformation of the gene products. A time-course microarray dataset from a yeast cell-cycle study is used for simulation assessment of the methods and real data analysis. The results show that our method, by considering both time lag and measurement scaling, performs much better than other linear and ODE models. It indicates the necessity of explicitly modeling the time lag and measurement scaling in ODE gene regulatory models.

Availability and implementation
R code is available at https://www.sta.cuhk.edu.hk/xfan/share/lagODE.zip.
出版社接受日期16.04.2020
著者Hu J., Qin H., Fan X.
期刊名稱Bioinformatics
出版年份2020
月份7
卷號36
期次13
出版社NLM (Medline)
出版地Oxford, England
頁次4058 - 4064
國際標準期刊號1367-4803
電子國際標準期刊號1460-2059
語言英式英語

上次更新時間 2020-28-11 於 00:09