Bioinformatics Advance Access originally published online on January 19, 2007
Bioinformatics 2007 23(6):755-763; doi:10.1093/bioinformatics/btl676
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Inferring pairwise regulatory relationships from multiple time series datasets
1Machine Learning Department, 2Language Technologies Institute, 3Computer Science Department and 4Department of Biological Sciences, Carnegie Mellon University, 5000 Forbes Ave., Pittsburgh, PA 15213, USA
*To whom correspondence should be addressed.
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Abstract |
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Motivation: Time series expression experiments have emerged as a popular method for studying a wide range of biological systems under a variety of conditions. One advantage of such data is the ability to infer regulatory relationships using time lag analysis. However, such analysis in a single experiment may result in many false positives due to the small number of time points and the large number of genes. Extending these methods to simultaneously analyze several time series datasets is challenging since under different experimental conditions biological systems may behave faster or slower making it hard to rely on the actual duration of the experiment.
Results: We present a new computational model and an associated algorithm to address the problem of inferring time-lagged regulatory relationships from multiple time series expression experiments with varying (unknown) time-scales. Our proposed algorithm uses a set of known interacting pairs to compute a temporal transformation between every two datasets. Using this temporal transformation we search for new interacting pairs. As we show, our method achieves a much lower false-positive rate compared to previous methods that use time series expression data for pairwise regulatory relationship discovery. Some of the new predictions made by our method can be verified using other high throughput data sources and functional annotation databases.
Availability: Matlab implementation is available from the supporting website: http://www.cs.cmu.edu/~yanxins/regulation_inference/index.html
Contact: zivbj{at}cs.cmu.edu
Supplementary information: Supplementary data are available at Bioinformatics online.
Associate Editor: Thomas Lengauer
Received on September 13, 2006; revised on December 18, 2006; accepted on January 4, 2007
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