Consistency Principle in Biological Dynamical Systems

author: Kunihiko Kaneko, Kaneko Laboratory, University of Tokyo
published: Nov. 29, 2007, recorded: October 2007, views: 359

Slides

Slides
0:00	Complex Systems Biology
0:54	Summary
1:26	Consistency between replication of molecules and
1:59	Toy Cell Model with Catalytic Reaction Network 'Crude but whole cell model‘
3:02	In continuum description, the following rate eqn., but we mostly use stochastic simulation
3:17	Toy Cell Model with Catalytic Reaction Network 'Crude but whole cell model‘
3:31	In continuum description, the following rate eqn., but we mostly use stochastic simulation
3:32	Growth speed and fidelity in replication
4:02	Toy Cell Model with Catalytic Reaction Network 'Crude but whole cell model‘
4:41	Growth speed and fidelity in replication
5:17	Traces: universal statistics
6:22	Formation of cascade catalytic reaction
6:28	Remarks
7:20	fluctuation by cells: distribution of each Ni by cells
8:54	Heuristic explanation of log-normal distribution - part 1
10:28	Heuristic explanation of log-normal distribution - part 2
10:39	Replicating artificial cell (experiment)
10:42	PhenotypicFluctuation
11:54	Standard population genetics - part 1
13:44	Standard population genetics - part 2
14:15	Standard population genetics - part 3
15:52	Standard population genetics - part 4
18:19	Partial （indiect) experimental confirmation - part 1
19:11	Partial （indiect) experimental confirmation - part 2
19:15	Partial （indiect) experimental confirmation - part 3
20:39	Partial （indiect) experimental confirmation - part 4
22:00	Confirmation by numerical evolution experiment by the reaction-net cell model
23:08	Confirmation of Fluctuation Dissipation Theorem by reaction-network cellmodel
23:24	Change of distribution
23:27	Phenotype fluct. (Vp) vsGene Fluct. (Vg) in the evolution of toy cell model
24:28	As μ (mutation rate) increases to μ max
25:20	??? to the theory
27:55	A simple model for Geno-Pheno relationship - part 1
28:26	A simple model for Geno-Pheno relationship - part 2
28:58	Discussion
30:43	Isologous Diversification - part 1
31:39	Isologous Diversification - part 2
32:27	Hierarchical differentiation from 'stem cell‘; by taking initially dynamics with instability (e.g., chaotic) - part 1
32:30	Hierarchical differentiation from 'stem cell‘; by taking initially dynamics with instability (e.g., chaotic) - part 2
32:32	Mechanism: approach to Milnor attractor?
32:36	Summary
33:56	Collaborators

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Description

We propose consistency principle between different levels, to understand a biological system. Three topics are discussed. First, as a result of consistency between molecule replication and cell reproduction, universal statistical laws on chemical abundances over cells are derived as also confirmed experimentally. They include power-law distribution of gene expressions,log-normal distribution of chemical abundances over cells, and embedding of the power law into the network connectivity. Second, as a result of consistency between gene and phenotype,a general relationship between phenotype fluctuations by genetic variation and isogenic phenotypic fluctuation by developmental noise is derived. Third, we touch upon the chaos mechanism for stem cell differentiation with autonomous regulation, as a result of consistency of cell reproduction and growth of cell ensemble.