The Importance of Computational Modeling in Stem Cell Research

Sol, Antonio del; Jung, Sascha

doi:10.1016/j.tibtech.2020.07.006

Cited by 35 publications

(11 citation statements)

References 63 publications

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“…or an overall distortion of the landscape (i.e., signal-driven). The application of appropriate computational models in systems biology can aid in uncovering the underlying mechanisms [100,101]. One of the most representative work is that Huang et al [59] modeled the bifurcation in hematopoiesis to reveal the lineage commitment quantitatively.…”

Section: Discussionmentioning

confidence: 99%

“…However, despite the widespread use of the Waddington landscape as a metaphor in experiments, there has been little examination into whether the fate decision observed in a particular experiment corresponds to a stochastic shift from one attractor to another on the landscape (i.e., noise-driven) or an overall distortion of the landscape (i.e., signal-driven). The application of appropriate computational models in systems biology can aid in uncovering the underlying mechanisms [100, 101]. One of the most representative work is that Huang et al [59] modeled the bifurcation in hematopoiesis to reveal the lineage commitment quantitatively.…”

Section: Discussionmentioning

confidence: 99%

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A Logic-incorporated Gene Regulatory Network Deciphers Principles in Cell Fate Decisions

Xue

Zhang

et al. 2023

Preprint

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Organisms utilize gene regulatory networks (GRNs) to make fate decisions, but the regulatory mechanisms of transcription factors (TFs) in GRNs are exceedingly intricate. A longstanding question in this field is how these tangled interactions synergistically contribute to decision-making procedures. To comprehensively understand the role of regulatory logic in cell fate decisions, we constructed a logic-incorporated GRN model and examined its behavior under two distinct driving forces (noise-driven and signal-driven). Under the noise-driven mode, we distilled the relationship among fate bias, regulatory logic, and noise profile. Under the signal-driven mode, we bridged regulatory logic and progression-accuracy trade-off, and uncovered distinctive trajectories of reprogramming influenced by logic motifs. In differentiation, we characterized a special logic-dependent priming stage by the solution landscape. Finally, we applied our findings to decipher three biological instances: hematopoiesis, embryogenesis, and trans-differentiation. Orthogonal to the classical analysis of expression profile, we harnessed noise patterns to construct the GRN corresponding to fate transition. Our work presents a generalizable framework for top-down fate-decision studies and a practical approach to the taxonomy of cell fate decisions.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

A Logic-incorporated Gene Regulatory Network Deciphers Principles in Cell Fate Decisions

Xue

Zhang

et al. 2023

Preprint

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“…The integration of computational modeling in stem cell-based tissue engineering therapies could dramatically increase our understanding into the causes of donor-to-donor variability and tissue remodeling outcomes, thereby helping the prediction of the in vivo evolution and providing superior preclinical and clinical performance of the resulting tissue-engineered prostheses. 49 By continuously adapting to the received mechanical stimuli, cells are known to be the drivers of tissue growth and remodeling mechanisms. 10 Evidence has shown that computational modeling at the cellular level has the opportunity to include factors mimicking cell–cell, cell–matrix, or cell–biomaterial interplay to explain in vivo phenomena.…”

Section: Computational Modeling Strategies For Precision Cardiovascul...mentioning

confidence: 99%

Combining Cell Technologies With Biomimetic Tissue Engineering Applications: A New Paradigm for Translational Cardiovascular Therapies

Motta

Martin

Gähwiler

et al. 2023

Stem Cells Translational Medicine

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Cardiovascular disease is a major cause of morbidity and mortality worldwide and, to date, the clinically available prostheses still present several limitations. The design of next-generation regenerative replacements either based on cellular or extracellular matrix technologies can address these shortcomings. Therefore, tissue engineered constructs could potentially become a promising alterative to the current therapeutic options for patients with cardiovascular diseases. In this review, we selectively present an overview of the current tissue engineering tools such as induced pluripotent stem cells, biomimetic materials, computational modeling, and additive manufacturing technologies, with a focus on their application to translational cardiovascular therapies. We discuss how these advanced technologies can help the development of biomimetic tissue engineered constructs and we finally summarize the latest clinical evidence for their use, and their potential therapeutic outcome.

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“…Mathematical modeling and advanced data processing techniques (e.g. artificial intelligence, and in particular deep learning) may make a difference [159][160][161][162] , by reducing the complexity of this task and predicting cell response patterns more reliably.…”

Section: Challenges In the Clinical Translation Of Ipsc-derived Skele...mentioning

confidence: 99%

Skeletal muscle differentiation of human iPSCs meets bioengineering strategies: perspectives and challenges

2022

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Although skeletal muscle repairs itself following small injuries, genetic diseases or severe damages may hamper its ability to do so. Induced pluripotent stem cells (iPSCs) can generate myogenic progenitors, but their use in combination with bioengineering strategies to modulate their phenotype has not been sufficiently investigated. This review highlights the potential of this combination aimed at pushing the boundaries of skeletal muscle tissue engineering. First, the overall organization and the key steps in the myogenic process occurring in vivo are described. Second, transgenic and non-transgenic approaches for the myogenic induction of human iPSCs are compared. Third, technologies to provide cells with biophysical stimuli, biomaterial cues, and biofabrication strategies are discussed in terms of recreating a biomimetic environment and thus helping to engineer a myogenic phenotype. The embryonic development process and the pro-myogenic role of the muscle-resident cell populations in co-cultures are also described, highlighting the possible clinical applications of iPSCs in the skeletal muscle tissue engineering field.

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The Importance of Computational Modeling in Stem Cell Research

Cited by 35 publications

References 63 publications

A Logic-incorporated Gene Regulatory Network Deciphers Principles in Cell Fate Decisions

A Logic-incorporated Gene Regulatory Network Deciphers Principles in Cell Fate Decisions

Combining Cell Technologies With Biomimetic Tissue Engineering Applications: A New Paradigm for Translational Cardiovascular Therapies

Skeletal muscle differentiation of human iPSCs meets bioengineering strategies: perspectives and challenges

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