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Combining Multiple Results of a Reverse-Engineering Algorithm: Application to the DREAM Five-Gene Network Challenge.
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- Author(s): Marbach, Daniel; Mattiussi, Claudio; Floreano, Dario
- Source:
Annals of the New York Academy of Sciences; Mar2009, Vol. 1158, p102-113, 12p, 1 Diagram, 5 Graphs- Subject Terms:
- Source:
- Additional Information
- Abstract: The output of reverse-engineering methods for biological networks is often not a single network prediction, but an ensemble of networks that are consistent with the experimentally measured data. In this paper, we consider the problem of combining the information contained within such an ensemble in order to (1) make more accurate network predictions and (2) estimate the reliability of these predictions. We review existing methods, discuss their limitations, and point out possible research directions toward more advanced methods for this purpose. The potential of considering ensembles of networks, rather than individual inferred networks, is demonstrated by showing how an ensemble voting method achieved winning performance on the Five-Gene Network Challenge of the second DREAM conference (Dialogue on Reverse Engineering Assessments and Methods 2007, New York, NY). [ABSTRACT FROM AUTHOR]
- Abstract: Copyright of Annals of the New York Academy of Sciences is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
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