ArticleBMC bioinformatics2013
Estimate hidden dynamic profiles of siRNA effect on apoptosis.
Article in BMC bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
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.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed.
- A survey on evolutionary algorithm based hybrid intelligence in bioinformatics.BioMed research international · 2014Review
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Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundFor the representation of RNA interference (RNAi) dynamics, several mathematical models based on systems of ordinary differential equations (ODEs) have been proposed. These models consist of equations for each molecule that are involved in RNAi phenomena. Therefore, many real-value parameters must be optimized to identify the models. They also have many 'hidden variables', which cannot be observed directly through experimentation. Calculation of the values of the hidden variables is generally very difficult, if not impossible in some special cases. Identification of the ODE models is also quite difficult.
resultsWe show that the simplified logistic Lotka-Volterra model, a well-established ODE model for biological and biochemical phenomena, can represent RNAi dynamics as a predator-prey system. Although a hidden variable exists in the model, its values can be determined and made visible as dynamic profiles of RNA-decomposing effects of siRNAs. Correlation analysis shows that the model parameters correlate highly with the total effect of the siRNA.
conclusionsThe results suggest that analyses using our model are useful to estimate dynamic profiles of siRNA effects on apoptosis and to score siRNA by its effects on apoptosis, namely 'phenotypic scoring'.
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