ArticleJournal of the Royal Society, Interface2008
Information-theoretic sensitivity analysis: a general method for credit assignment in complex networks.
Article in Journal of the Royal Society, Interface, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
18 citing papers in PubMed.
- Concepts and Applications of Information Theory to Immuno-Oncology.Trends in cancer · 2021Review
- An optimal control approach for enhancing natural killer cells' secretion of cytolytic molecules.APL bioengineering · 2020Article
- Optimal Microbiome Networks: Macroecology and Criticality.Entropy (Basel, Switzerland) · 2019Article
- Uncertainty quantification, propagation and characterization by Bayesian analysis combined with global sensitivity analysis applied to dynamical intracellular pathway models.Bioinformatics (Oxford, England) · 2019Article
- Examining the Impacts of Urban Form on Air Pollution in Developing Countries: A Case Study of China's Megacities.International journal of environmental research and public health · 2018Article
- Stochastic Pharmacokinetic-Pharmacodynamic Modeling for Assessing the Systemic Health Risk of Perfluorooctanoate (PFOA).Toxicological sciences : an official journal of the Society of Toxicology · 2018Article
- Optimal information networks: Application for data-driven integrated health in populations.Science advances · 2018Article
- Mathematical model identifies effective P53 accumulation with target gene binding affinity in DNA damage response for cell fate decision.Cell cycle (Georgetown, Tex.) · 2018Article
- Use of social network analysis and global sensitivity and uncertainty analyses to better understand an influenza outbreak.Oncotarget · 2017Article
- Driver fatigue detection through multiple entropy fusion analysis in an EEG-based system.PloS one · 2017Article
- Computational modeling of sphingolipid metabolism.BMC systems biology · 2015Article
- Parametric sensitivity analysis for biochemical reaction networks based on pathwise information theory.BMC bioinformatics · 2013Article
- Design of an expert system for mitigating trace element toxicity in cancer risk management.Cancer informatics · 2013Article
- Towards a unifying, systems biology understanding of large-scale cellular death and destruction caused by poorly liganded iron: Parkinson's, Huntington's, Alzheimer's, prions, bactericides, chemical toxicology and others as examples.Archives of toxicology · 2010Review
- Neural correlations, decisions, and actions.Current opinion in neurobiology · 2010Review
- Propagation of kinetic uncertainties through a canonical topology of the TLR4 signaling network in different regions of biochemical reaction space.Theoretical biology & medical modelling · 2010Article
- Iron behaving badly: inappropriate iron chelation as a major contributor to the aetiology of vascular and other progressive inflammatory and degenerative diseases.BMC medical genomics · 2009Article
- A new strategy for assessing sensitivities in biochemical models.Philosophical transactions. Series A, Mathematical, physical, and engineering sciences · 2008Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Most systems can be represented as networks that couple a series of nodes to each other via one or more edges, with typically unknown equations governing their quantitative behaviour. A major question then pertains to the importance of each of the elements that act as system inputs in determining the output(s). We show that any such system can be treated as a 'communication channel' for which the associations between inputs and outputs can be quantified via a decomposition of their mutual information into different components characterizing the main effect of individual inputs and their interactions. Unlike variance-based approaches, our novel methodology can easily accommodate correlated inputs.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.