Nicola Soranzo - Dissemin

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Papers authored by Nicola Soranzo

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2010 Andrea Pinna, Nicola Soranzo

ORCID

, Alberto de la Fuente

From Knockouts to Networks: Establishing Direct Cause-Effect Relationships through Graph Analysis

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G. Iacono, C. Altafini, F. Ramezani, N. Soranzo

ORCID

Determining the distance to monotonicity of a biological network: A graph-theoretical approach

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This paper was not found in any repository; the policy of its publisher is unknown or unclear.

2009 Nicola Soranzo

ORCID

Systems biology approaches to the dynamics of gene expression and chemical reactions

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Fahimeh Ramezani, Giovanni Iacono, Nicola Soranzo

ORCID

, Claudio Altafini

On the distance to monotonicity of a biological network: A graph-theoretical approach

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Nicola Soranzo

ORCID

, Mattia Zampieri, Lorenzo Farina

ORCID

, Claudio Altafini

mRNA stability and the unfolding of gene expression in the long-period yeast metabolic cycle

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Nicola Soranzo

ORCID

, Claudio Altafini

ERNEST: a toolbox for chemical reaction network theory

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2008 Mattia Zampieri, Nicola Soranzo

ORCID

, Daniele Bianchini, Claudio Altafini

Origin of Co-Expression Patterns in E.coli and S.cerevisiae Emerging from Reverse Engineering Algorithms

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Mattia Zampieri, Nicola Soranzo

ORCID

, Claudio Altafini

Discerning static and causal interactions in genome-wide reverse engineering problems

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M. Zampieri, N. Soranzo

ORCID

, C. Altafini

Modeling the genome-wide transient response to stimuli in yeast: Adaptation through integral feedback

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This paper was not found in any repository; the policy of its publisher is unknown or unclear.

2007 Mattia Zampieri, Nicola Soranzo

ORCID

, Daniele Bianchini, Claudio Altafini

Network inference from gene expression profiles: what "physical" network are we seeing?

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Nicola Soranzo

ORCID

, Ginestra Bianconi, Claudio Altafini

Comparing association network algorithms for reverse engineering of large-scale gene regulatory networks: Synthetic versus real data

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Nicola Soranzo

ORCID

, Ginestra Bianconi, Claudio Altafini

Linear and nonlinear methods for gene regulatory network inference

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