Abstract
Systematic gene expression analyses provide comprehensive
information about the transcriptional responseto different
environmental and developmental conditions. With enough gene
expression data points,computational biologists may eventually
generate predictive computer models of transcription
regulation.Such models will require computational methodologies
consistent with the behavior of known biologicalsystems that
remain tractable. We represent regulatory relationships between
genes as linear coefficients orweights, with the "net" regulation
influence on a gene's expression being the mathematical summation
of theindependent regulatory inputs. Test regulatory networks
generated with this approach display stable andcyclically stable
gene expression levels, consistent with known biological systems.
We include variables tomodel the effect of environmental
conditions on transcription regulation and observed various
alterations ingene expression patterns in response to
environmental input. Finally, we use a derivation of this
modelsystem to predict the regulatory network from simulated
input/output data sets and find that it accuratelypredicts all
components of the model, even with noisy expression data.
Original language | English |
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Title of host publication | Pacific Symposium on Biocomputing '99, Proceedings |
Place of Publication | River Edge |
Publisher | World Scientific |
Publication date | 1999 |
Pages | 112-23 |
Publication status | Published - 1999 |
Event | Pacific Symposium on Biocomputing, January 4 - 9 - Mauna Lani, Hawaii Duration: 1 Jan 1999 → … |
Conference
Conference | Pacific Symposium on Biocomputing, January 4 - 9 |
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City | Mauna Lani, Hawaii |
Period | 01/01/1999 → … |