ArticleGenome research2003
Toward rigorous comprehension of biological complexity: modeling, execution, and visualization of thymic T-cell maturation.
Article in Genome research, 2003. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 32 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
32 citing papers in PubMed.
- The Future Exploring of Gut Microbiome-Immunity Interactions: From In Vivo/Vitro Models to In Silico Innovations.Microorganisms · 2024Review
- Towards early diagnosis of Alzheimer's disease: advances in immune-related blood biomarkers and computational approaches.Frontiers in immunology · 2024Review
- Verifiable biology.Journal of the Royal Society, Interface · 2023Review
- Modeling the Dynamics of T-Cell Development in the Thymus.Entropy (Basel, Switzerland) · 2021Review
- The evolution of universal adaptations of life is driven by universal properties of matter: energy, entropy, and interaction.F1000Research · 2020Article
- Epidermal Growth Factor Signaling towards Proliferation: Modeling and Logic Inference Using Forward and Backward Search.BioMed research international · 2017Article
- The tumor as an organ: comprehensive spatial and temporal modeling of the tumor and its microenvironment.BMC bioinformatics · 2016Article
- Emergent stem cell homeostasis in the C. elegans germline is revealed by hybrid modeling.Biophysical journal · 2015Article
- An Interactive Tool for Animating Biology, and Its Use in Spatial and Temporal Modeling of a Cancerous Tumor and Its Microenvironment.PloS one · 2015Article
- Modelling biological behaviours with the unified modelling language: an immunological case study and critique.Journal of the Royal Society, Interface · 2014Article
- Logic programming to predict cell fate patterns and retrodict genotypes in organogenesis.Journal of the Royal Society, Interface · 2014Article
- Dynamical and Mechanistic Reconstructive Approaches of T Lymphocyte Dynamics: Using Visual Modeling Languages to Bridge the Gap between Immunologists, Theoreticians, and Programmers.Frontiers in immunology · 2013Review
- Spartan: a comprehensive tool for understanding uncertainty in simulations of biological systems.PLoS computational biology · 2013Article
- The bottom-up approach to defining life: deciphering the functional organization of biological cells via multi-objective representation of biological complexity from molecules to cells.Frontiers in physiology · 2013Article
- Conceptual Model-based Systems Biology: mapping knowledge and discovering gaps in the mRNA transcription cycle.PloS one · 2012Article
- Systems immunology: a survey of modeling formalisms, applications and simulation tools.Immunologic research · 2012Review
- Modeling gene regulatory network motifs using Statecharts.BMC bioinformatics · 2012Article
- Cell-cycle regulation of NOTCH signaling during C. elegans vulval development.Molecular systems biology · 2012Article
- Modeling formalisms in Systems Biology.AMB Express · 2011Article
- Discrete diffusion models to study the effects of Mg2+ concentration on the PhoPQ signal transduction system.BMC genomics · 2010Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
One of the problems biologists face is a data set too large to comprehend in full. Experimenters generate data at an ever-growing pace, each from their own niche of interest. Current theories are each able, at best, to capture and model only a small part of the data. We aim to develop a general approach to modeling that will help broaden biological understanding. T-cell maturation in the thymus is a telling example of the accumulation of experimental data into a large disconnected data set. The thymus is responsible for the maturation of stem cells into mature T cells, and its complexity divides research into different fields, for example, cell migration, cell differentiation, histology, electron microscopy, biochemistry, molecular biology, and more. Each field forms its own viewpoint and its own set of data. In this study we present the results of a comprehensive integration of large parts of this data set. The integration is performed in a two-tiered visual manner. First, we use the visual language of Statecharts, which makes specification precise, legible, and executable on computers. We then set up a moving graphical interface that dynamically animates the cells, their receptors, the different gradients, and the interactions that constitute thymic maturation. This interface also provides a means for interacting with the simulation.
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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.