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It works on temporal series of gene activation data and, using genetic programming, it extracts the activation functions of the different genes from those data.
It works on temporal series of gene activation data and, using genetic programming, it extracts the activation functions of the different genes from those data.
We present a new reverse-engineering framework for gene regulatory network reconstruction. It works on temporal series of gene activation data and, ...
A New Evolutionary Gene Regulatory Network Reverse Engineering Tool. https ... Genetic Programming Framework for the Reverse Engineering of Gene Regulatory ...
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In this review, we summarize and categorize the main frameworks and methods currently available for inferring transcriptional regulatory networks from ...
This paper presents a new system, called GeNet, which aims at overcoming the main limitations of GRNGen, by directly evolving entire networks using ...
This paper presents GENECI (GEne NEtwork Consensus Inference), an evolutionary machine learning approach that acts as an organizer for constructing ensembles.
Feb 8, 2008 · In this work, we developed Evolutionary Algorithms (EA) to learn network structures and we applied our strategies to learn a regulatory network, ...
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Jul 21, 2015 · Reverse engineering Gene Regulatory Network is the process of representing the genetic interactions given by time-series data with an ...
Abstract. Motivation: Estimating gene regulatory networks over biological lineages is central to a deeper understanding of how cells evolve during development ...