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Will systems biology offer new holistic paradigms to life sciences?

Conti F, Valerio MC, Zbilut JP, Giuliani A - Syst Synth Biol (2008)

Bottom Line: A biological system, like any complex system, blends stochastic and deterministic features, displaying properties of both.In a certain sense, this blend is exactly what we perceive as the "essence of complexity" given we tend to consider as non-complex both an ideal gas (fully stochastic and understandable at the statistical level in the thermodynamic limit of a huge number of particles) and a frictionless pendulum (fully deterministic relative to its motion).In this commentary we make the statement that systems biology will have a relevant impact on nowadays biology if (and only if) will be able to capture the essential character of this blend that in our opinion is the generation of globally ordered collective modes supported by locally stochastic atomisms.

View Article: PubMed Central - PubMed

Affiliation: Chemistry Department, University of Rome, 'La Sapienza', Rome, Italy.

ABSTRACT
A biological system, like any complex system, blends stochastic and deterministic features, displaying properties of both. In a certain sense, this blend is exactly what we perceive as the "essence of complexity" given we tend to consider as non-complex both an ideal gas (fully stochastic and understandable at the statistical level in the thermodynamic limit of a huge number of particles) and a frictionless pendulum (fully deterministic relative to its motion). In this commentary we make the statement that systems biology will have a relevant impact on nowadays biology if (and only if) will be able to capture the essential character of this blend that in our opinion is the generation of globally ordered collective modes supported by locally stochastic atomisms.

No MeSH data available.


The Figure reports the correlation between the values of expression of around 23,000 genes (the vector points of the figure) relative to two different populations of blood cells (macrophages) bearing a mutation as for a very important gene involved in innate immunity (Myd88ko) and wild type respectively. Pearson r (product moment correlation coefficient) between the gene expression vectors of the two populations is near the maximum attainable (r = 0.998)
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Fig1: The Figure reports the correlation between the values of expression of around 23,000 genes (the vector points of the figure) relative to two different populations of blood cells (macrophages) bearing a mutation as for a very important gene involved in innate immunity (Myd88ko) and wild type respectively. Pearson r (product moment correlation coefficient) between the gene expression vectors of the two populations is near the maximum attainable (r = 0.998)

Mentions: The most evident and macroscopic collective phenomena asking for consideration is with no doubt the existence of an extremely reproducible characteristic level of expression for all the many thousands of genes of a cell line. Figure 1 reports the correlations of two different strains of the same cell line (mouse macrophages wild type and Myd88 knock out, respectively) with the vector points representing the expression level of approximately 23,000 gene products (Hirotani et al. 2005). The correlation between the two cell samples, spanning the whole genome expression is remarkable, and this kind of behaviour is encountered every time, in any microarray experiment, whenever two different populations of the same cell line (notwithstanding which stressor, drug or mutation is inserted) are plotted. This invariance is what constitutes the individuality of a given cell line and we are far from the understanding of the bases of such an ordered and repeatable behaviour that is practically unique in biology. What is for sure is that this is a “scalable” behaviour, reproducible with random extractions of genes up to a certain minimum number and with no relation to the specific functions of the involved gene products. This extremely ordered behaviour (that has its counterpart in time constituted by the presence of whole genome rhythms spanning billions of cells in a colony, thus falsifying the ergodic hypothesis (each cell in a plate makes its own game) at the basis of “molecular first” hypotheses) (Tsuchiya et al. 2007; Klevecz et al. 2004) is evident when reaching a minimum number of considered genes. When we look inside the single gene behaviours we observe erratic variability not consistent with the large scale ordering. An examination of Fig. 1 immediately explains this conundrum: looking at exceptional behaviour of single genes corresponds to picking up (and considering it as the relevant information) the points escaping the linear relation at a larger extent (the genes significantly affected by treatment), but these points are very few and, still more important, these erratic points are where the influence of noise is maximal so that it is perfectly sound that we cannot derive from them a reliable information.Fig. 1


Will systems biology offer new holistic paradigms to life sciences?

Conti F, Valerio MC, Zbilut JP, Giuliani A - Syst Synth Biol (2008)

The Figure reports the correlation between the values of expression of around 23,000 genes (the vector points of the figure) relative to two different populations of blood cells (macrophages) bearing a mutation as for a very important gene involved in innate immunity (Myd88ko) and wild type respectively. Pearson r (product moment correlation coefficient) between the gene expression vectors of the two populations is near the maximum attainable (r = 0.998)
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC2553325&req=5

Fig1: The Figure reports the correlation between the values of expression of around 23,000 genes (the vector points of the figure) relative to two different populations of blood cells (macrophages) bearing a mutation as for a very important gene involved in innate immunity (Myd88ko) and wild type respectively. Pearson r (product moment correlation coefficient) between the gene expression vectors of the two populations is near the maximum attainable (r = 0.998)
Mentions: The most evident and macroscopic collective phenomena asking for consideration is with no doubt the existence of an extremely reproducible characteristic level of expression for all the many thousands of genes of a cell line. Figure 1 reports the correlations of two different strains of the same cell line (mouse macrophages wild type and Myd88 knock out, respectively) with the vector points representing the expression level of approximately 23,000 gene products (Hirotani et al. 2005). The correlation between the two cell samples, spanning the whole genome expression is remarkable, and this kind of behaviour is encountered every time, in any microarray experiment, whenever two different populations of the same cell line (notwithstanding which stressor, drug or mutation is inserted) are plotted. This invariance is what constitutes the individuality of a given cell line and we are far from the understanding of the bases of such an ordered and repeatable behaviour that is practically unique in biology. What is for sure is that this is a “scalable” behaviour, reproducible with random extractions of genes up to a certain minimum number and with no relation to the specific functions of the involved gene products. This extremely ordered behaviour (that has its counterpart in time constituted by the presence of whole genome rhythms spanning billions of cells in a colony, thus falsifying the ergodic hypothesis (each cell in a plate makes its own game) at the basis of “molecular first” hypotheses) (Tsuchiya et al. 2007; Klevecz et al. 2004) is evident when reaching a minimum number of considered genes. When we look inside the single gene behaviours we observe erratic variability not consistent with the large scale ordering. An examination of Fig. 1 immediately explains this conundrum: looking at exceptional behaviour of single genes corresponds to picking up (and considering it as the relevant information) the points escaping the linear relation at a larger extent (the genes significantly affected by treatment), but these points are very few and, still more important, these erratic points are where the influence of noise is maximal so that it is perfectly sound that we cannot derive from them a reliable information.Fig. 1

Bottom Line: A biological system, like any complex system, blends stochastic and deterministic features, displaying properties of both.In a certain sense, this blend is exactly what we perceive as the "essence of complexity" given we tend to consider as non-complex both an ideal gas (fully stochastic and understandable at the statistical level in the thermodynamic limit of a huge number of particles) and a frictionless pendulum (fully deterministic relative to its motion).In this commentary we make the statement that systems biology will have a relevant impact on nowadays biology if (and only if) will be able to capture the essential character of this blend that in our opinion is the generation of globally ordered collective modes supported by locally stochastic atomisms.

View Article: PubMed Central - PubMed

Affiliation: Chemistry Department, University of Rome, 'La Sapienza', Rome, Italy.

ABSTRACT
A biological system, like any complex system, blends stochastic and deterministic features, displaying properties of both. In a certain sense, this blend is exactly what we perceive as the "essence of complexity" given we tend to consider as non-complex both an ideal gas (fully stochastic and understandable at the statistical level in the thermodynamic limit of a huge number of particles) and a frictionless pendulum (fully deterministic relative to its motion). In this commentary we make the statement that systems biology will have a relevant impact on nowadays biology if (and only if) will be able to capture the essential character of this blend that in our opinion is the generation of globally ordered collective modes supported by locally stochastic atomisms.

No MeSH data available.