# IET Systems Biology

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Displaying Results 1 - 7 of 7
• ### Optimal control for probabilistic boolean networks

Publication Year: 2010, Page(s):99 - 107
Cited by:  Papers (5)
| | PDF (314 KB)

Aberrant gene functions usually contribute to the pathology or diseases. Avoiding undesirable cellular phenotypes as many as possible is a major purpose of external control for gene regulatory networks. An interesting question is how to control a gene network subjected to the condition that the genes reach some undesirable states with minimal probability during a cell cycle. In this paper, we make... View full abstract»

• ### Generalisation of a procedure for computing transcription factor profiles

Publication Year: 2010, Page(s):108 - 118
| | PDF (397 KB)

The limited amount of quantitative experimental data generated from life-science experiments poses a major challenge in systems biology. The reason for this is that many systems approaches, such as parameter estimation, simulation and sensitivity analysis make use of models or analyse quantitative data. However, these techniques are only of limited use if only qualitative or semi-quantitative info... View full abstract»

• ### Parameter identification, experimental design and model falsification for biological network models using semidefinite programming

Publication Year: 2010, Page(s):119 - 130
Cited by:  Papers (3)
| | PDF (481 KB)

One of the most challenging tasks in systems biology is parameter identification from experimental data. In particular, if the available data are noisy, the resulting parameter uncertainty can be huge and should be quantified. In this work, a set-based approach for parameter identification in discrete time models of biochemical reaction networks from time series data is developed. The basic idea i... View full abstract»

• ### Hidden variable analysis of transcription factor cooperativity from microarray time courses

Publication Year: 2010, Page(s):131 - 144
| | PDF (1113 KB)

Gene expression is regulated by transcription factor activity, which can be extremely difficult to measure directly. Previous work has established a method to extract the hidden transcription factor activity profile from microarray data and use it to effectively identify genes that are targets of a single transcription factor. However, most genes are regulated by two or more transcription factor... View full abstract»

• ### Inference of gene regulatory networks using S-system: a unified approach

Publication Year: 2010, Page(s):145 - 156
Cited by:  Papers (22)
| | PDF (616 KB)

With the increased availability of DNA microarray time-series data, it is possible to discover dynamic gene regulatory networks (GRNs). S-system is a promising model to capture the rich dynamics of GRNs. However, owing to the complexity of the inference problem and limited number of available data comparing to the number of unknown kinetic parameters, S-system can only be applied to a very small G... View full abstract»

• ### Time-dependent regulation of yeast glycolysis upon nitrogen starvation depends on cell history

Publication Year: 2010, Page(s):157 - 168
| | PDF (654 KB)

In this study, the authors investigated how the glycolytic flux was regulated in time upon nitrogen starvation of cells with different growth histories. We have compared cells grown in glucose-limited chemostat cultures under respiratory conditions (low dilution rate of 0.1/h) to cells grown under respirofermentative conditions (high dilution rate of 0.35/h). The fermentative capacity was lower in... View full abstract»

• ### Robustness of the Drosophila segment polarity network to transient perturbations

Publication Year: 2010, Page(s):169 - 176
| | PDF (222 KB)

Continuous and Boolean models for the Drosophila segment polarity network have shown that the system is able to maintain the wild-type pattern when subjected to sustained changes in the interaction parameters and initial conditions. Embryo development is likely to occur under fluctuating environmental conditions. Here, a well-established Boolean model is used to explore the ability of the s... View full abstract»

## Aims & Scope

IET Systems Biology covers intra- and inter-cellular dynamics, using systems- and signal-oriented approaches.

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IET Research Journals
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