ArticlePLoS computational biology2016
A Network Model to Describe the Terminal Differentiation of B Cells.
Article in PLoS computational biology, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 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
39 citing papers in PubMed, 60 citations in OpenAlex.
- Quantitative systems pharmacology model of B cell immune response in mouse.Frontiers in immunology · 2026Article
- Computational modelling of aggressive B-cell lymphoma.Biochemical Society transactions · 2025Review
- Using Monoids for the Integration of Genomic and Metabolic Parameters in the Prediction of Phenotypes in Regulatory Cascades.bioRxiv : the preprint server for biology · 2025Article
- A system-level model reveals that transcriptional stochasticity is required for hematopoietic stem cell differentiation.NPJ systems biology and applications · 2024Article
- Canalizing kernel for cell fate determination.Briefings in bioinformatics · 2024Article
- scBoolSeq: Linking scRNA-seq statistics and Boolean dynamics.PLoS computational biology · 2024Article
- Regulus infers signed regulatory relations from few samples' information using discretization and likelihood constraints.PLoS computational biology · 2024Article
- A multiscale spatial modeling framework for the germinal center response.Frontiers in immunology · 2024Article
- Relative importance of composition structures and biologically meaningful logics in bipartite Boolean models of gene regulation.Scientific reports · 2022Article
- Termination of CD40L co-stimulation promotes human B cell differentiation into antibody-secreting cells.European journal of immunology · 2022Article
- Executable models of immune signaling pathways in HIV-associated atherosclerosis.NPJ systems biology and applications · 2022Article
- Balance between immunoregulatory B cells and plasma cells drives pancreatic tumor immunity.Cell reports. Medicine · 2022Article
- Identification of dynamic driver sets controlling phenotypical landscapes.Computational and structural biotechnology journal · 2022Article
- Boolean modeling reveals that cyclic attractors in macrophage polarization serve as reservoirs of states to balance external perturbations from the tumor microenvironment.Frontiers in immunology · 2022Article
- Patient-Specific Modeling of Diffuse Large B-Cell Lymphoma.Biomedicines · 2021Article
- Gene regulatory networks exhibit several kinds of memory: quantification of memory in biological and random transcriptional networks.iScience · 2021Article
- Integrating Patient-Specific Information into Logic Models of Complex Diseases: Application to Acute Myeloid Leukemia.Journal of personalized medicine · 2021Article
- Establishment of the TBX-code reveals aberrantly activated T-box gene TBX3 in Hodgkin lymphoma.PloS one · 2021Article
- Transcriptional and Microenvironmental Landscape of Macrophage Transition in Cancer: A Boolean Analysis.Frontiers in immunology · 2021Article
- Establishment of the TALE-code reveals aberrantly activated homeobox gene PBX1 in Hodgkin lymphoma.PloS one · 2021Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Terminal differentiation of B cells is an essential process for the humoral immune response in vertebrates and is achieved by the concerted action of several transcription factors in response to antigen recognition and extracellular signals provided by T-helper cells. While there is a wealth of experimental data regarding the molecular and cellular signals involved in this process, there is no general consensus regarding the structure and dynamical properties of the underlying regulatory network controlling this process. We developed a dynamical model of the regulatory network controlling terminal differentiation of B cells. The structure of the network was inferred from experimental data available in the literature, and its dynamical behavior was analyzed by modeling the network both as a discrete and a continuous dynamical systems. The steady states of these models are consistent with the patterns of activation reported for the Naive, GC, Mem, and PC cell types. Moreover, the models are able to describe the patterns of differentiation from the precursor Naive to any of the GC, Mem, or PC cell types in response to a specific set of extracellular signals. We simulated all possible single loss- and gain-of-function mutants, corroborating the importance of Pax5, Bcl6, Bach2, Irf4, and Blimp1 as key regulators of B cell differentiation process. The model is able to represent the directional nature of terminal B cell differentiation and qualitatively describes key differentiation events from a precursor cell to terminally differentiated B cells.
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.