Algebraic and geometric understanding of cells: Epigenetic inheritance of phenotypes between generations

Research output: Chapter in Book/Report/Conference proceedingChapter

5 Citations (Scopus)

Abstract

We have developed methods and systems for analyzing epigenetic information in cells, as well as that of genetic information, to expand our understanding of how living systems are determined. Because cells are minimum units reflecting epigenetic information, which is considered to map the history of a parallel-processing recurrent network of biochemical reactions, their behaviors cannot be explained by considering only conventional DNA informationprocessing events. The role of epigenetic information in cells, which complements their genetic information, was inferred by comparing predictions from genetic information with cell behavior observed under conditions chosen to reveal adaptation processes and community effects. A system for analyzing epigenetic information was developed starting from the twin complementary viewpoints of cell regulation as an 'algebraic' system (emphasis on temporal aspects) and as a 'geometric' system (emphasis on spatial aspects). The knowledge acquired from this study may lead to the use of cells that fully control practical applications like cell-based drug screening and the regeneration of organs.

Original languageEnglish
Title of host publicationHigh Resolution Microbial Single Cell Analytics
Pages55-81
Number of pages27
DOIs
Publication statusPublished - 2011 Nov 29
Externally publishedYes

Publication series

NameAdvances in Biochemical Engineering/Biotechnology
Volume124
ISSN (Print)0724-6145

Keywords

  • Algebraic viewpoint
  • Epigenetic information
  • Geometric viewpoint
  • Individuality
  • On-chip single-cell-based cultivation/analysis

ASJC Scopus subject areas

  • Biotechnology
  • Bioengineering
  • Applied Microbiology and Biotechnology

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  • Cite this

    Yasuda, K. (2011). Algebraic and geometric understanding of cells: Epigenetic inheritance of phenotypes between generations. In High Resolution Microbial Single Cell Analytics (pp. 55-81). (Advances in Biochemical Engineering/Biotechnology; Vol. 124). https://doi.org/10.1007/10_2010_97