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Gene network inference using a swarm intelligence framework

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TLDR
In this paper, a model-based approach is adopted, according to which the quality of a candidate architecture is evaluated by assessing the ability of the corresponding trained model to reproduce the available dynamics.
Abstract
In this paper, we present a framework for inferring gene regulatory networks from gene expression time series. A model-based approach is adopted, according to which the quality of a candidate architecture is evaluated by assessing the ability of the corresponding trained model to reproduce the available dynamics. Candidate architectures are generated in the context of the ant colony optimization (ACO) meta-heuristic and model training is performed using particle swarm optimization (PSO). We propose a novel solution construction heuristic for artificial ants, based on growth and preferential attachment, in order to generate candidate structures that adhere to well-known gene network properties. Preliminary results using an artificial network demonstrate the potential of the framework to infer the underlying network architecture to a promising degree of success.

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Book ChapterDOI

A Multiobjective Phenomic Algorithm for Inference of Gene Networks

TL;DR: An evolutionary algorithm for reconstructing gene networks from expression data using phenotypic interactions, thereby avoiding the need for an explicit objective function is presented and applied to the yeast sporulation dataset.
References
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Journal ArticleDOI

Network biology: understanding the cell's functional organization

TL;DR: This work states that rapid advances in network biology indicate that cellular networks are governed by universal laws and offer a new conceptual framework that could potentially revolutionize the view of biology and disease pathologies in the twenty-first century.
Journal ArticleDOI

Network Motifs: Simple Building Blocks of Complex Networks

TL;DR: Network motifs, patterns of interconnections occurring in complex networks at numbers that are significantly higher than those in randomized networks, are defined and may define universal classes of networks.
Journal ArticleDOI

Lethality and centrality in protein networks

TL;DR: It is demonstrated that the phenotypic consequence of a single gene deletion in the yeast Saccharomyces cerevisiae is affected to a large extent by the topological position of its protein product in the complex hierarchical web of molecular interactions.
Journal ArticleDOI

Modeling and simulation of genetic regulatory systems: a literature review.

TL;DR: This paper reviews formalisms that have been employed in mathematical biology and bioinformatics to describe genetic regulatory systems, in particular directed graphs, Bayesian networks, Boolean networks and their generalizations, ordinary and partial differential equations, qualitative differential equation, stochastic equations, and so on.
Journal ArticleDOI

Computational systems biology

Hiroaki Kitano
- 14 Nov 2002 - 
TL;DR: The reviews in this Insight cover many different aspects of this energetic field, although all, in one way or another, illuminate the functioning of modular circuits, including their robustness, design and manipulation.
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