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Dynamic modeling of gene expression dataWe describe the time evolution of gene expression levels by using a time translational matrix to predict future expression levels of genes based on their expression levels at some initial time. We deduce the time translational matrix for previously published DNA microarray gene expression data sets by modeling them within a linear framework by using the characteristic modes obtained by singular value decomposition. The resulting time translation matrix provides a measure of the relationships among the modes and governs their time evolution. We show that a truncated matrix linking just a few modes is a good approximation of the full time translation matrix. This finding suggests that the number of essential connections among the genes is small.
Document ID
20040112588
Acquisition Source
Legacy CDMS
Document Type
Reprint (Version printed in journal)
External Source(s)
Authors
Holter, N. S.
(University Park PA 16802, United States)
Maritan, A.
Cieplak, M.
Fedoroff, N. V.
Banavar, J. R.
Date Acquired
August 21, 2013
Publication Date
February 13, 2001
Publication Information
Publication: Proceedings of the National Academy of Sciences of the United States of America
Volume: 98
Issue: 4
ISSN: 0027-8424
Subject Category
Life Sciences (General)
Distribution Limits
Public
Copyright
Other
Keywords
NASA Discipline Plant Biology
Non-NASA Center

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