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Collective motions and specific effectors: a statistical mechanics perspective on biological regulation.

Giuliani A - BMC Genomics (2010)

Bottom Line: This will allow to both obtain a general frame of reference for rationalizing the burden of data coming from high throughput technologies and to derive effective operational views on biological systems.The network paradigm in which microscopic level elements (nodes) are each other related by functional links so giving rise to both global (entire network) and local (specific) behavior is a promising metaphor to try and develop a statistical mechanics inspired approach for biological systems.The need to complement the purely molecular view with mesoscopic approaches is evident in all the studied examples that in turn demonstrate the untenability of the simple ergodic approach dominant in molecular biology in which the data coming from huge ensemble of cells are considered as relative to a single 'average' cell.

View Article: PubMed Central - HTML - PubMed

Affiliation: Environment and Health Department, Istituto Superiore di Sanità, Viale Regina Elena 299, Roma, Italy. alessandro.giuliani@iss.it

ABSTRACT

Background: The interaction of a multiplicity of scales in both time and space is a fundamental feature of biological systems. The complementation of macroscopic (entire organism) and microscopic (molecular biology) views with a mesoscopic level of analysis able to connect the different planes of investigation is urgently needed. This will allow to both obtain a general frame of reference for rationalizing the burden of data coming from high throughput technologies and to derive effective operational views on biological systems.

Results: The network paradigm in which microscopic level elements (nodes) are each other related by functional links so giving rise to both global (entire network) and local (specific) behavior is a promising metaphor to try and develop a statistical mechanics inspired approach for biological systems. Here we show the application of this paradigm to different systems going from yeast metabolism to murine macrophages response to immune stimulation.

Conclusions: The need to complement the purely molecular view with mesoscopic approaches is evident in all the studied examples that in turn demonstrate the untenability of the simple ergodic approach dominant in molecular biology in which the data coming from huge ensemble of cells are considered as relative to a single 'average' cell.

Show MeSH
The first component of the variation in time of different gene choice is reported as for free growing yeast colonies. Pc1small corresponds to a choice of 60 genes connected to ribogenesis, pc1whole to the entire genome, pc1rand to a random extraction of 275 genes. It is worth noting the superposition of the time courses and the practical invariance of the percent of explained variance of the extracted mode.
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Figure 3: The first component of the variation in time of different gene choice is reported as for free growing yeast colonies. Pc1small corresponds to a choice of 60 genes connected to ribogenesis, pc1whole to the entire genome, pc1rand to a random extraction of 275 genes. It is worth noting the superposition of the time courses and the practical invariance of the percent of explained variance of the extracted mode.

Mentions: Figure 3 reports the first principal component of gene expression as measured in freely growing yeast colonies and computed over different choices of genes. While metabolic cycles in yeast colonies were already very well known and associated to the alternation of ‘reductive’ and ‘oxidative’ phases [16], in this case the relevant feature of the observed cycles was their independence of any specific biological function of the involved gene products. The same time course of the first principal component of gene expression was observed with different choices of gene probes, going from the whole genome, to ribogenesis related genes and random gene extractions. This implies the impossibility to get rid of this phenomenon in terms of specific gene functionalities or cell physiology features and the need to think of a sort of ‘ecology-in-a-plate’ arising from the interaction of many cells living together and interacting each other and thus asking for a different kind of ‘statistics’ with respect to the simple ‘average cell hypothesis’ implicit in the classical molecular paradigm [17]. The observed behavior is analogous to the behavior of paramagnetic substances (e.g spin glasses) which acquire specific macroscopic organization thanks to the existence of preferred orientations of nearby elementary units (e.g. dipoles) [7].


Collective motions and specific effectors: a statistical mechanics perspective on biological regulation.

Giuliani A - BMC Genomics (2010)

The first component of the variation in time of different gene choice is reported as for free growing yeast colonies. Pc1small corresponds to a choice of 60 genes connected to ribogenesis, pc1whole to the entire genome, pc1rand to a random extraction of 275 genes. It is worth noting the superposition of the time courses and the practical invariance of the percent of explained variance of the extracted mode.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC2822530&req=5

Figure 3: The first component of the variation in time of different gene choice is reported as for free growing yeast colonies. Pc1small corresponds to a choice of 60 genes connected to ribogenesis, pc1whole to the entire genome, pc1rand to a random extraction of 275 genes. It is worth noting the superposition of the time courses and the practical invariance of the percent of explained variance of the extracted mode.
Mentions: Figure 3 reports the first principal component of gene expression as measured in freely growing yeast colonies and computed over different choices of genes. While metabolic cycles in yeast colonies were already very well known and associated to the alternation of ‘reductive’ and ‘oxidative’ phases [16], in this case the relevant feature of the observed cycles was their independence of any specific biological function of the involved gene products. The same time course of the first principal component of gene expression was observed with different choices of gene probes, going from the whole genome, to ribogenesis related genes and random gene extractions. This implies the impossibility to get rid of this phenomenon in terms of specific gene functionalities or cell physiology features and the need to think of a sort of ‘ecology-in-a-plate’ arising from the interaction of many cells living together and interacting each other and thus asking for a different kind of ‘statistics’ with respect to the simple ‘average cell hypothesis’ implicit in the classical molecular paradigm [17]. The observed behavior is analogous to the behavior of paramagnetic substances (e.g spin glasses) which acquire specific macroscopic organization thanks to the existence of preferred orientations of nearby elementary units (e.g. dipoles) [7].

Bottom Line: This will allow to both obtain a general frame of reference for rationalizing the burden of data coming from high throughput technologies and to derive effective operational views on biological systems.The network paradigm in which microscopic level elements (nodes) are each other related by functional links so giving rise to both global (entire network) and local (specific) behavior is a promising metaphor to try and develop a statistical mechanics inspired approach for biological systems.The need to complement the purely molecular view with mesoscopic approaches is evident in all the studied examples that in turn demonstrate the untenability of the simple ergodic approach dominant in molecular biology in which the data coming from huge ensemble of cells are considered as relative to a single 'average' cell.

View Article: PubMed Central - HTML - PubMed

Affiliation: Environment and Health Department, Istituto Superiore di Sanità, Viale Regina Elena 299, Roma, Italy. alessandro.giuliani@iss.it

ABSTRACT

Background: The interaction of a multiplicity of scales in both time and space is a fundamental feature of biological systems. The complementation of macroscopic (entire organism) and microscopic (molecular biology) views with a mesoscopic level of analysis able to connect the different planes of investigation is urgently needed. This will allow to both obtain a general frame of reference for rationalizing the burden of data coming from high throughput technologies and to derive effective operational views on biological systems.

Results: The network paradigm in which microscopic level elements (nodes) are each other related by functional links so giving rise to both global (entire network) and local (specific) behavior is a promising metaphor to try and develop a statistical mechanics inspired approach for biological systems. Here we show the application of this paradigm to different systems going from yeast metabolism to murine macrophages response to immune stimulation.

Conclusions: The need to complement the purely molecular view with mesoscopic approaches is evident in all the studied examples that in turn demonstrate the untenability of the simple ergodic approach dominant in molecular biology in which the data coming from huge ensemble of cells are considered as relative to a single 'average' cell.

Show MeSH