Why network approach can promote a new way of thinking in biology

Giuliani, Alessandro; Filippi, Sandra; Bertolaso, Marta

doi:10.3389/fgene.2014.00083

Cited by 57 publications

(50 citation statements)

References 29 publications

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“…This scientific stance takes the name of "middle-out" approach since it focuses on a mesoscopic level maximizing the correlations among system descriptors. In other words, this approach lies "in the middle" between pure "bottom-up" (the causally relevant layer is the microscopic one) and "top-down" (the causally relevant layer is where general laws are defined) approaches [9,10].…”

Section: Introductionmentioning

confidence: 99%

What Differentiates Poor and Good Outcome Psychotherapy? A Statistical-Mechanics-Inspired Approach to Psychotherapy Research

Felice

Orsucci

Scozzari

et al. 2019

Systems

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Statistical mechanics investigates how emergent properties of macroscopic systems (such as temperature and pressure) relate to microscopic state fluctuations. The underlying idea is that global statistical descriptors of order and variability can monitor the relevant dynamics of the whole system at hand. Here we test the possibility of extending such an approach to psychotherapy research investigating the possibility of predicting the outcome of psychotherapy on the sole basis of coarse-grained empirical macro-parameters. Four good-outcome and four poor-outcome brief psychotherapies were recorded, and their transcripts coded in terms of standard psychological categories (abstract, positive emotional and negative emotional language pertaining to patient and therapist). Each patient-therapist interaction is considered as a discrete multivariate time series made of subsequent word-blocks of 150-word length, defined in terms of the above categories. “Static analyses” (Principal Component Analysis) highlighted a substantial difference between good-outcome and poor-outcome cases in terms of mutual correlations among those descriptors. In the former, the patient’s use of abstract language correlated with therapist’s emotional negative language, while in the latter it co-varied with therapist’s emotional positive language, thus showing the different judgment of the therapists regarding the same variable (abstract language) in poor and good outcome cases. On the other hand, the “dynamic analyses”, based on five coarse-grained descriptors related to variability, the degree of order and complexity of the series, demonstrated a relevant case-specific effect, pointing to the possibility of deriving a consistent picture of any single psychotherapeutic process. Overall, the results showed that the systemic approach to psychotherapy (an old tenet of psychology) is mature enough to shift from a metaphorical to a fully quantitative status.

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Section: Introductionmentioning

confidence: 99%

What Differentiates Poor and Good Outcome Psychotherapy? A Statistical-Mechanics-Inspired Approach to Psychotherapy Research

Felice

Orsucci

Scozzari

et al. 2019

Systems

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“…Providing descriptive characterizations of complex systems has a long history in the field of (complex) dynamical systems and chaos theory [32,50,68]. Describing (complex) systems by means of graphs is ubiquitous in modern science and engineering disciplines [12,15,18,19,22,26,33,51,56,69]. In fact, graphs offer a sound mathematical framework to describe the relations/causality among the interacting elements of the system under analysis.…”

Section: Introductionmentioning

confidence: 99%

Characterization of Graphs for Protein Structure Modeling and Recognition of Solubility

Livi¹,

Giuliani²,

Sadeghian³

2016

CBIO

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This paper deals with the relations among structural, topological, and chemical properties of the E.Coli proteome from the vantage point of the solubility/aggregation propensity of proteins. Each E.Coli protein is initially represented according to its known folded 3D shape. This step consists in representing the available E.Coli proteins in terms of graphs. We first analyze those graphs by considering pure topological characterizations, i.e., by analyzing the mass fractal dimension and the distribution underlying both shortest paths and vertex degrees. Results confirm the general architectural principles of proteins. Successively, we focus on the statistical properties of a representation of such graphs in terms of vectors composed of several numerical features, which we extracted from their structural representation. We found that protein size is the main discriminator for the solubility, while however there are other factors that help explaining the solubility degree. We finally analyze such data through a novel one-class classifier, with the aim of discriminating among very and poorly soluble proteins. Results are encouraging and consolidate the potential of pattern recognition techniques when employed to describe complex biological systems.

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“…Network thinking provides the ability to simplify complex problems without losing their essential features. Because this approach is experimentally constrained and computationally accessible, it is heuristically very useful (Giuliani et al, ). Indeed, below we present novel emergent properties that would not be otherwise evident.…”

Section: Resultsmentioning

confidence: 99%

CMV‐induced embryonic mouse organ of corti dysplasia: Network architecture of dysfunctional lateral inhibition

Melnick

Jaskoll

2015

Birth Defects Research

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Congenital CMV infection is the major non-genetic cause of sensorineural hearing loss at birth and beyond. Among other pathologies, there is a striking dysplasia/hyperplasia of organ of Corti hair and supporting cells (HC/SC). Using an in vitro embryonic mouse model of CMV-induced cochlear teratogenesis that mimics the known human pathology, and functional signaling network modeling, we tested the hypothesis that CMV disrupts the highly ordered HC/SC pattern by dysregulating Notch and Fgfr3, their cognate ligands and downstream effectors. Several novel emergent properties of the critical lateral inhibition subnetwork became apparent. The subnetwork has classic small-world properties such as short paths between most gene pairs, few long-distance links, and considerable clustering. Concomitantly, the calculated probability that our specific gene expression dataset is from dysplastic organs of Corti is highly significant (p < 1 × 10−12). Further, we determined that the subnetwork has a highly heterogeneous scale-free topology in which the highly linked genes (hubs), Notch and Fgfr3, play a central role in mediating interactions among the less linked genes. This phenomenon has important biologic and therapeutic implications.

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Why network approach can promote a new way of thinking in biology

Cited by 57 publications

References 29 publications

What Differentiates Poor and Good Outcome Psychotherapy? A Statistical-Mechanics-Inspired Approach to Psychotherapy Research

What Differentiates Poor and Good Outcome Psychotherapy? A Statistical-Mechanics-Inspired Approach to Psychotherapy Research

Characterization of Graphs for Protein Structure Modeling and Recognition of Solubility

CMV‐induced embryonic mouse organ of corti dysplasia: Network architecture of dysfunctional lateral inhibition

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