ArticleCytotechnology2003
Towards predictive models of stem cell fate.
Article in Cytotechnology, 2003. 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
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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.
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Who cites it
16 citing papers in PubMed.
- Stem cell-based approaches for developmental neurotoxicity testing.Frontiers in toxicology · 2024Review
- The recent advances in the mathematical modelling of human pluripotent stem cells.SN applied sciences · 2020Review
- Quantifying intrinsic and extrinsic control of single-cell fates in cancer and stem/progenitor cell pedigrees with competing risks analysis.Scientific reports · 2016Article
- Investigating biocomplexity through the agent-based paradigm.Briefings in bioinformatics · 2015Review
- Influence of the microenvironment on cell fate determination and migration.Physiological genomics · 2014Review
- Article
- Predicting clonal self-renewal and extinction of hematopoietic stem cells.Proceedings of the National Academy of Sciences of the United States of America · 2011Article
- Computational models reduce complexity and accelerate insight into cardiac signaling networks.Circulation research · 2011Review
- Scalable stirred-suspension bioreactor culture of human pluripotent stem cells.Tissue engineering. Part A · 2010Review
- Dynamic hematological disease: a review.Journal of mathematical biology · 2009Review
- Multiway modeling and analysis in stem cell systems biology.BMC systems biology · 2008Article
- Pathogenesis, treatment effects, and resistance dynamics in chronic myeloid leukemia--insights from mathematical model analyses.Journal of molecular medicine (Berlin, Germany) · 2008Review
- Mathematical model for chemotherapeutic drug efficacy in arresting tumour growth based on the cancer stem cell hypothesis.Cell proliferation · 2007Article
- Mathematical model for the cancer stem cell hypothesis.Cell proliferation · 2006Article
- The GOD of hematopoietic stem cells: a clonal diversity model of the stem cell compartment.Cell cycle (Georgetown, Tex.) · 2006Article
- Asymmetry of stem cell fate and the potential impact of the niche: observations, simulations, and interpretations.Stem cell reviews · 2006Review
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Quantitative approaches are essential for the advancement of strategies to manipulate stem cells or their derivatives for therapeutic applications. Predictive models of stem cell systems would provide the means to pose and validate non-intuitive hypotheses and could thus serve as an important tool for discerning underlying regulatory mechanisms governing stem cell fate decisions. In this paper we review the development of computational models that attempt to describe mammalian adult and embryonic stem (ES) cell responses. Early stochastic models that relied exclusively on statistical distributions to describe the in vitro or in vivo output of stem cells are being revised to incorporate the contributions of exogenous and endogenous parameters on specific stem cell fate processes. Recent models utilize cell specific data (for example, cell-surface receptor distributions, transcription factor half-lives, cell-cycle status, etc.) to provide mechanistic descriptions that are consistent with biologically observed phenomena. Ultimately, the goal of these computational models is to, a priori, predict stem cell output given an initial set of conditions. Our efforts to develop a predictive model of ES cell fate are discussed. The quantitative studies presented in this review represent an important step in developing bioengineering approaches to characterize and predict stem cell behavior. Ongoing efforts to incorporate genetic and signaling network data into computational models should accelerate our understanding of fundamental principles governing stem cell fate decisions.
Identifiers
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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.