dorsal/arxiv
View SchemaSymmetry and Dynamics in living organisms: The self-similarity principle governs gene expression dynamics
| Authors | T. Ochiai, J. C. Nacher, T. Akutsu |
|---|---|
| Categories | |
| ArXiv ID | q-bio/0503003 |
| URL | https://arxiv.org/abs/q-bio/0503003 |
Abstract
The ambitious and ultimate research purpose in Systems Biology is the understanding and modelling of the cell's system. Although a vast number of models have been developed in order to extract biological knowledge from complex systems composed of basic elements as proteins, genes and chemical compounds, a need remains for improving our understanding of dynamical features of the systems (i.e., temporal-dependence). In this article, we analyze the gene expression dynamics (i.e., how the genes expression fluctuates in time) by using a new constructive approach. This approach is based on only two fundamental ingredients: symmetry and the Markov property of dynamics. First, by using experimental data of human and yeast gene expression time series, we found a symmetry in short-time transition probability from time $t$ to time $t+1$. We call it self-similarity symmetry (i.e., surprisingly, the gene expression short-time fluctuations contain a repeating pattern of smaller and smaller parts that are like the whole, but different in size). Secondly, the Markov property of dynamics reflects that the short-time fluctuation governs the full-time behaviour of the system. Here, we succeed in reconstructing naturally the global behavior of the observed distribution of gene expression (i.e., scaling-law) and the local behaviour of the power-law tail of this distribution, by using only these two ingredients: symmetry and the Markov property of dynamics. This approach may represent a step forward toward an integrated image of the basic elements of the whole cell.
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"abstract": "The ambitious and ultimate research purpose in Systems Biology is the\nunderstanding and modelling of the cell\u0027s system. Although a vast number of\nmodels have been developed in order to extract biological knowledge from\ncomplex systems composed of basic elements as proteins, genes and chemical\ncompounds, a need remains for improving our understanding of dynamical features\nof the systems (i.e., temporal-dependence).\n In this article, we analyze the gene expression dynamics (i.e., how the genes\nexpression fluctuates in time) by using a new constructive approach. This\napproach is based on only two fundamental ingredients: symmetry and the Markov\nproperty of dynamics. First, by using experimental data of human and yeast gene\nexpression time series, we found a symmetry in short-time transition\nprobability from time $t$ to time $t+1$. We call it self-similarity symmetry\n(i.e., surprisingly, the gene expression short-time fluctuations contain a\nrepeating pattern of smaller and smaller parts that are like the whole, but\ndifferent in size). Secondly, the Markov property of dynamics reflects that the\nshort-time fluctuation governs the full-time behaviour of the system. Here, we\nsucceed in reconstructing naturally the global behavior of the observed\ndistribution of gene expression (i.e., scaling-law) and the local behaviour of\nthe power-law tail of this distribution, by using only these two ingredients:\nsymmetry and the Markov property of dynamics. This approach may represent a\nstep forward toward an integrated image of the basic elements of the whole\ncell.",
"arxiv_id": "q-bio/0503003",
"authors": [
"T. Ochiai",
"J. C. Nacher",
"T. Akutsu"
],
"categories": [
"q-bio.BM"
],
"title": "Symmetry and Dynamics in living organisms: The self-similarity principle governs gene expression dynamics",
"url": "https://arxiv.org/abs/q-bio/0503003"
},
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