Literature DB >> 18178225

Mathematical classification of regulatory logics for compound environmental changes.

Reiko J Tanaka1, Hidenori Kimura.   

Abstract

This paper is concerned with biological regulatory mechanisms in response to the simultaneous occurrence of a huge number of environmental changes. The restricted resources of cells strictly limit the number of their regulatory methods; hence, cells must adopt, as compensation, special mechanisms to deal with the simultaneous occurrence of environmental changes. We hypothesize that cells use various control logics to integrate information about independent environmental changes related to a cell task and represent the resulting effects of the different ways of integration by logical functions. Using the notion of equivalence classes in set theory, we describe the mathematical classification of the effects into biologically unequivalent ones realized by different control logics. Our purely mathematical and systematic classification of logical functions reveals three elementary control logics with different biological relevance. To better understand their biological significance, we consider examples of biological systems that use these elementary control logics.

Mesh:

Year:  2007        PMID: 18178225     DOI: 10.1016/j.jtbi.2007.11.023

Source DB:  PubMed          Journal:  J Theor Biol        ISSN: 0022-5193            Impact factor:   2.691


  3 in total

1.  Optimal control of gene mutation in DNA replication.

Authors:  Juanyi Yu; Jr-Shin Li; Tzyh-Jong Tarn
Journal:  J Biomed Biotechnol       Date:  2012-01-22

2.  Motor Control System for Adaptation of Healthy Individuals and Recovery of Poststroke Patients: A Case Study on Muscle Synergies.

Authors:  Fady S Alnajjar; Juan C Moreno; Ken-Ichi Ozaki; Izumi Kondo; Shingo Shimoda
Journal:  Neural Plast       Date:  2019-03-27       Impact factor: 3.599

3.  Muscle synergy space: learning model to create an optimal muscle synergy.

Authors:  Fady Alnajjar; Tytus Wojtara; Hidenori Kimura; Shingo Shimoda
Journal:  Front Comput Neurosci       Date:  2013-10-15       Impact factor: 2.380

  3 in total

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