ReviewFrontiers in bioengineering and biotechnology2018
Computational Modeling and Reverse Engineering to Reveal Dominant Regulatory Interactions Controlling Osteochondral Differentiation: Potential for Regenerative Medicine.
Review in Frontiers in bioengineering and biotechnology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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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.
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Who cites it
10 citing papers in PubMed.
- Computational methods for biofabrication in tissue engineering and regenerative medicine - a literature review.Computational and structural biotechnology journal · 2024Review
- scBoolSeq: Linking scRNA-seq statistics and Boolean dynamics.PLoS computational biology · 2024Article
- Contributions of cell behavior to geometric order in embryonic cartilage.PLoS computational biology · 2023Article
- Review
- Regulatory network-based model to simulate the biochemical regulation of chondrocytes in healthy and osteoarthritic environments.Scientific reports · 2022Article
- Inferring causal gene regulatory networkFrontiers in bioengineering and biotechnology · 2022Article
- Turning Nature's own processes into design strategies for living bone implant biomanufacturing: a decade of Developmental Engineering.Advanced drug delivery reviews · 2021Review
- Using a Digital Twin of an Electrical Stimulation Device to Monitor and Control the Electrical Stimulation of CellsFrontiers in bioengineering and biotechnology · 2021Article
- Technique of Gene Expression Profiles Extraction Based on the Complex Use of Clustering and Classification Methods.Diagnostics (Basel, Switzerland) · 2020Article
- Use of Computational Modeling to Study Joint Degeneration: A Review.Frontiers in bioengineering and biotechnology · 2020Review
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The specialization of cartilage cells, or chondrogenic differentiation, is an intricate and meticulously regulated process that plays a vital role in both bone formation and cartilage regeneration. Understanding the molecular regulation of this process might help to identify key regulatory factors that can serve as potential therapeutic targets, or that might improve the development of qualitative and robust skeletal tissue engineering approaches. However, each gene involved in this process is influenced by a myriad of feedback mechanisms that keep its expression in a desirable range, making the prediction of what will happen if one of these genes defaults or is targeted with drugs, challenging. Computer modeling provides a tool to simulate this intricate interplay from a network perspective. This paper aims to give an overview of the current methodologies employed to analyze cell differentiation in the context of skeletal tissue engineering in general and osteochondral differentiation in particular. In network modeling, a network can either be derived from mechanisms and pathways that have been reported in the literature (knowledge-based approach) or it can be inferred directly from the data (data-driven approach). Combinatory approaches allow further optimization of the network. Once a network is established, several modeling technologies are available to interpret dynamically the relationships that have been put forward in the network graph (implication of the activation or inhibition of certain pathways on the evolution of the system over time) and to simulate the possible outcomes of the established network such as a given cell state. This review provides for each of the aforementioned steps (building, optimizing, and modeling the network) a brief theoretical perspective, followed by a concise overview of published works, focusing solely on applications related to cell fate decisions, cartilage differentiation and growth plate biology. Particular attention is paid to an in-house developed example of gene regulatory network modeling of growth plate chondrocyte differentiation as all the aforementioned steps can be illustrated. In summary, this paper discusses and explores a series of tools that form a first step toward a rigorous and systems-level modeling of osteochondral differentiation in the context of regenerative medicine.
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Registered trials
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