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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.

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Related in: MedlinePlus

The picture reports the microarray derived differential gene expression values correspondent to two samples of the same cell kind. They refer to 22690 ORFs and span four order of magnitudes of expression levels.
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Figure 2: The picture reports the microarray derived differential gene expression values correspondent to two samples of the same cell kind. They refer to 22690 ORFs and span four order of magnitudes of expression levels.

Mentions: On a practical ground, the common experience of any experimentalist dealing with microarray data is the fact that any two independent samples of the same cell kind when correlated over the expression of more or less twenty thousands different gene products display a near to unity correlation (see Figure 2).


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

Giuliani A - BMC Genomics (2010)

The picture reports the microarray derived differential gene expression values correspondent to two samples of the same cell kind. They refer to 22690 ORFs and span four order of magnitudes of expression levels.
© Copyright Policy - open-access
Related In: Results  -  Collection

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

Figure 2: The picture reports the microarray derived differential gene expression values correspondent to two samples of the same cell kind. They refer to 22690 ORFs and span four order of magnitudes of expression levels.
Mentions: On a practical ground, the common experience of any experimentalist dealing with microarray data is the fact that any two independent samples of the same cell kind when correlated over the expression of more or less twenty thousands different gene products display a near to unity correlation (see Figure 2).

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
Related in: MedlinePlus