Abstract:
:Various biological processes exhibit characteristics that vary dramatically in response to different input conditions or changes in the history of the process itself. One of the examples studied here, the Ras-PKC-mitogen-activated protein kinase (MAPK) bistable pathway, follows two distinct dynamics (modes) depending on duration and strength of EGF stimulus. Similar examples are found in the behavior of the cell cycle and the immune system. A classification methodology, based on time-frequency analysis, was developed and tested on these systems to understand global behavior of biological processes. Contrary to most traditionally used statistical and spectral methods, our approach captures complex functional relations between parts of the systems in a simple way. The resulting algorithms are capable of analyzing and classifying sets of time-series data obtained from in vivo or in vitro experiments, or in silico simulation of biological processes. The method was found to be considerably stable under stochastic noise perturbation and, therefore, suitable for the analysis of real experimental data.
journal_name
Proc Natl Acad Sci U S Aauthors
Barbano PE,Spivak M,Feng J,Antoniotti M,Mishra Bdoi
10.1073/pnas.0500554102keywords:
subject
Has Abstractpub_date
2005-05-03 00:00:00pages
6245-50issue
18eissn
0027-8424issn
1091-6490pii
0500554102journal_volume
102pub_type
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