Stem Cell Networks
We present a general computational theory of stem cell networks and their developmental dynamics. Stem cell networks are special cases of developmental control networks. Our theory generates a natural classification of all possible stem cell networks based on their network architecture. Each stem cell network has a unique topology and semantics and developmental dynamics that result in distinct phenotypes. We show that the ideal growth dynamics of multicellular systems generated by stem cell networks have mathematical properties related to the coefficients of Pascal's Triangle. The relationship to cancer stem cells and their control networks is indicated. The theory lays the foundation for a new research paradigm for understanding and investigating stem cells. The theory of stem cell networks implies that new methods for generating and controlling stem cells will become possible.
Code (0)
등록된 구현이 없습니다.
Similar Papers 제목 키워드 기반
Progress towards quantitative design principles of multicellular systems
Living systems, particularly multicellular systems, often seem hopelessly complex. But recent studies have suggested that beneath this complexity, there may be unifying quantitative principles that we are only now starti…
DiversityCo-existence of Micro, Pico and Atto Cells in Optical Wireless Communication
Interference between cells or users can have a significant impact on the quality of optical wireless communication (OWC) links. This paper studies the co-existence of infrared based Micro cells with Visible light communi…
DiversityPICODecoding the mechanisms underlying cell-fate decision-making during stem cell differentiation by Random Circuit Perturbation
Stem cells can precisely and robustly undergo cellular differentiation and lineage commitment, referred to as stemness. However, how the gene network underlying stemness regulation reliably specifies cell fates is not we…
Decision MakingComplexity in cancer stem cells and tumor evolution: towards precision medicine
In this review, we discuss recent advances on the plasticity of cancer stem cells and highlight their relevance to understand the metastatic process and to guide therapeutic interventions. Recent results suggest that the…
Using single-cell entropy to describe the dynamics of reprogramming and differentiation of induced pluripotent stem cells
Induced pluripotent stem cells (iPSCs) provide a great model to study the process of reprogramming and differentiation of stem cells. Single-cell RNA sequencing (scRNA-seq) enables us to investigate the reprogramming pro…