ArticleJournal of computational biology : a journal of computational molecular cell biology2014
Describing the complexity of systems: multivariable "set complexity" and the information basis of systems biology.
Article in Journal of computational biology : a journal of computational molecular cell biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 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
16 citing papers in PubMed.
- Mutual information-based best linear unbiased prediction for enhanced genomic prediction accuracy.Journal of animal science · 2025Article
- Laplacian Spectra of Persistent Structures in Taiwan, Singapore, and US Stock Markets.Entropy (Basel, Switzerland) · 2023Article
- Higher-Order Interactions and Their Duals Reveal Synergy and Logical Dependence beyond Shannon-Information.Entropy (Basel, Switzerland) · 2023Article
- Article
- LARGE-SCALE MULTIPLE INFERENCE OF COLLECTIVE DEPENDENCE WITH APPLICATIONS TO PROTEIN FUNCTION.The annals of applied statistics · 2021Article
- Toward an Information Theory of Quantitative Genetics.Journal of computational biology : a journal of computational molecular cell biology · 2021Article
- Cerebrospinal Fluid MicroRNA Changes in Cognitively Normal Veterans With a History of Deployment-Associated Mild Traumatic Brain Injury.Frontiers in neuroscience · 2021Article
- Partial Information Decomposition and the Information Delta: A Geometric Unification Disentangling Non-Pairwise Information.Entropy (Basel, Switzerland) · 2020Article
- Article
- Computational Inference Software for Tetrad Assembly from Randomly Arrayed Yeast Colonies.G3 (Bethesda, Md.) · 2019Article
- Next Generation Networks: Featuring the Potential Role of Emerging Applications in Translational Oncology.Journal of clinical medicine · 2019Article
- Multivariate Analysis of Data Sets with Missing Values: An Information Theory-Based Reliability Function.Journal of computational biology : a journal of computational molecular cell biology · 2019Article
- Symmetries among Multivariate Information Measures Explored Using Möbius Operators.Entropy (Basel, Switzerland) · 2019Article
- Groupwise image registration based on a total correlation dissimilarity measure for quantitative MRI and dynamic imaging data.Scientific reports · 2018Article
- The Information Content of Discrete Functions and Their Application in Genetic Data Analysis.Journal of computational biology : a journal of computational molecular cell biology · 2017Article
- Biological data analysis as an information theory problem: multivariable dependence measures and the shadows algorithm.Journal of computational biology : a journal of computational molecular cell biology · 2015Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Context dependence is central to the description of complexity. Keying on the pairwise definition of "set complexity," we use an information theory approach to formulate general measures of systems complexity. We examine the properties of multivariable dependency starting with the concept of interaction information. We then present a new measure for unbiased detection of multivariable dependency, "differential interaction information." This quantity for two variables reduces to the pairwise "set complexity" previously proposed as a context-dependent measure of information in biological systems. We generalize it here to an arbitrary number of variables. Critical limiting properties of the "differential interaction information" are key to the generalization. This measure extends previous ideas about biological information and provides a more sophisticated basis for the study of complexity. The properties of "differential interaction information" also suggest new approaches to data analysis. Given a data set of system measurements, differential interaction information can provide a measure of collective dependence, which can be represented in hypergraphs describing complex system interaction patterns. We investigate this kind of analysis using simulated data sets. The conjoining of a generalized set complexity measure, multivariable dependency analysis, and hypergraphs is our central result. While our focus is on complex biological systems, our results are applicable to any complex system.
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.