Cell fates as high-dimensional attractor states of a complex gene regulatory network.

Multistability and Multicellularity: Cell Fates as High-dimensional Attractors of Gene Regulatory Networks

The Relationship between Microscopic and Collective Properties in Gene Regulatory Network-based Morphogenetic Systems

Gene regulatory network (GRN)-based morphogenetic systems have recently attracted an increasing attention in artificial life and morphogenetic engineering research. However, the relationship between microscopic properties of intracellular GRNs and collective properties of morphogenetic systems has not been fully explored yet. Thus, we propose a new GRN-based framework to elucidate how critical ...

Comparison of MLP NN Approach with PCA and ICA for Extraction of Hidden Regulatory Signals in Biological Networks

The biologists now face with the masses of high dimensional datasets generated from various high-throughput technologies, which are outputs of complex inter-connected biological networks at different levels driven by a number of hidden regulatory signals. So far, many computational and statistical methods such as PCA and ICA have been employed for computing low-dimensional or hidden represe...

Dynamics inside the cancer cell attractor reveal cell heterogeneity, limits of stability, and escape.

The observed intercellular heterogeneity within a clonal cell population can be mapped as dynamical states clustered around an attractor point in gene expression space, owing to a balance between homeostatic forces and stochastic fluctuations. These dynamics have led to the cancer cell attractor conceptual model, with implications for both carcinogenesis and new therapeutic concepts. Immortaliz...

Epigenetic Landscapes Explain Partially Reprogrammed Cells and Identify Key Reprogramming Genes

A common metaphor for describing development is a rugged "epigenetic landscape" where cell fates are represented as attracting valleys resulting from a complex regulatory network. Here, we introduce a framework for explicitly constructing epigenetic landscapes that combines genomic data with techniques from spin-glass physics. Each cell fate is a dynamic attractor, yet cells can change fate in ...