ArticleJournal of theoretical biology2009
Transcription factor network reconstruction using the living cell array.
Article in Journal of theoretical biology, 2009. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
6 citing papers in PubMed.
- Understanding Physiology in the Continuum: Integration of Information from Multiple -Frontiers in pharmacology · 2017Article
- Microengineered cell and tissue systems for drug screening and toxicology applications: Evolution ofTechnology · 2015Article
- Dynamic transcription factor activity profiling in 2D and 3D cell cultures.Biotechnology and bioengineering · 2013Article
- Optimality and thermodynamics determine the evolution of transcriptional regulatory networks.Molecular bioSystems · 2012Article
- Comparison of the cytokine and chemokine dynamics of the early inflammatory response in models of burn injury and infection.Cytokine · 2011Article
- NETWORKS, BIOLOGY AND SYSTEMS ENGINEERING: A CASE STUDY IN INFLAMMATION.Computers & chemical engineering · 2009Article
Corrections and comments
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Authors and funding
3 authors.
Funding
Abstract
The objective of identifying transcriptional regulatory networks is to provide insights as to what governs an organism's long term response to external stimuli. We explore the coupling of the living cell array (LCA), a novel microfluidics device which utilizes fluorescence levels as a surrogate for transcription factor activity with reverse Euler deconvolution (RED) a computational technique proposed in this work to decipher the dynamics of the interactions. It is hypothesized that these two methods will allow us to first assess the underlying network architecture associated with the transcription factor network as well as specific mechanistic consequences of transcription factor activation such as receptor dimerization or tolerance. The overall approach identifies evidence of time-lagged response which may be indicative of mechanisms such as receptor dimerization, tolerance mechanisms which are evidence of various receptor mediated dynamics, and feedback loops which regulate the response of an organism to changing environmental conditions. Furthermore, through the exploration of multiple network architectures, we were able to obtain insights as to the role each transcription factor plays in the overall response and their overall redundancy in the organism's response to external perturbations. Thus, the LCA along with the proposed analysis technique is a valuable tool for identifying the possible architectures and mechanisms underlying the transcriptional response.
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Registered trials
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