Natalie Berestovsky's research while affiliated with Rice University and other places

Publications (3)

Article
Full-text available
The behavior and phenotypic changes of cells are governed by a cellular circuitry that represents a set of biochemical reactions. Based on biological functions, this circuitry is divided into three types of networks, each encoding for a major biological process: signal transduction, transcription regulation, and metabolism. This division has genera...
Article
Full-text available
Regulatory networks play a central role in cellular behavior and decision making. Learning these regulatory networks is a major task in biology, and devising computational methods and mathematical models for this task is a major endeavor in bioinformatics. Boolean networks have been used extensively for modeling regulatory networks. In this model,...
Article
Full-text available
Recent advances in high-throughput technologies and an increased knowledge of biochemical systems have enabled the reconstruction of cellular regulatory networks. While these reconstructions often consist of the connectivity patterns among the network's components, an important task in this area is to derive values for the kinetic parameters of the...

Citations

... Hybridizing deterministic Boolean and stochastic Petri net descriptions together offers advantages of developing extremely large-scale, multi-omics simulations with minimal parameterization. In an early example [21], the integration of two disjoint modeling forms was performed through the assignment of triplets, in which the places in the Petri net were associated with variables in the Boolean system. The drawback of such "stitching" is that the Petri-to-Boolean conversion requires an assigned threshold for conversion between 1 and 0. Furthermore, the Boolean-to-Petri conversion (largely representing the lag in transcription and translation resulting in changes in metabolite and protein levels) must handle difference in timescales of the networks; Berestovsky et al introduced delays by queuing the triplet for evaluation at a delayed time before updating the Boolean variable. ...
... The latter require a precise assessment of kinetic parameter values, which are often hard or even impossible to obtain, especially when dealing with large networks. On the other hand, we can use Boolean networks to simulate the dynamics of gene regulatory networks even when the values of kinetic parameters are unknown [15]. Boolean genetic model presents a simple representation suitable for large scale gene regulatory networks [16,17,18]. ...