In this paper, we suggest a new approach for reverse engineering gene regulatory networks, which consists of using a reconstruction process that is similar to the evolutionary process that created these networks. The aim is to integrate prior knowledge into the reverse engineering procedure, thus biasing the search towards biologically plausible solutions. To this end, we propose an evolutionary method that abstracts and mimics the natural evolution of gene regulatory networks. Our method can be used with a wide range of nonlinear dynamical models. This allows us to explore novel model types such as the log-sigmoid model introduced here. To allow direct comparison with other methods, we use a benchmark dataset from an in vivo synthetic-biol...
Background The evolution of high throughput technologies that measure gene expression levels has cr...
This work appears to complement an existingproject, Bio-inpired reverse engineering of regula-tory ...
Inferring gene networks is a daunting task. We here describe several algorithms we used in the Dialo...
The expression of genes is controlled by regulatory networks, which perform fundamental information ...
Reverse engineering methods are typically first tested on simulated data from in silico networks, fo...
Reverse engineering methods are typically first tested on simulated data from in silico networks, fo...
There is an urgent need for tools to unravel the complex interactions and functionalities of genes. ...
Inferring transcriptional gene regulatory networks from transcriptomic datasets is a key challenge o...
This work appears to complement an existing project, ”Bio-inpired reverse engineering of regulatory...
Experimental innovations starting in the 1990’s leading to the advent of high-throughput experiments...
Reverse engineering of gene networks aims at revealing the structure of the gene regulation network ...
The quest to determine cause from effect is often referred to as reverse engineering in the context ...
The paper describes the problem of discovering genetic networks from time course gene expression dat...
International audienceBACKGROUND: Inferring gene regulatory networks from data requires the developm...
This is the final version of the article. Available from the publisher via the DOI in this record.Un...
Background The evolution of high throughput technologies that measure gene expression levels has cr...
This work appears to complement an existingproject, Bio-inpired reverse engineering of regula-tory ...
Inferring gene networks is a daunting task. We here describe several algorithms we used in the Dialo...
The expression of genes is controlled by regulatory networks, which perform fundamental information ...
Reverse engineering methods are typically first tested on simulated data from in silico networks, fo...
Reverse engineering methods are typically first tested on simulated data from in silico networks, fo...
There is an urgent need for tools to unravel the complex interactions and functionalities of genes. ...
Inferring transcriptional gene regulatory networks from transcriptomic datasets is a key challenge o...
This work appears to complement an existing project, ”Bio-inpired reverse engineering of regulatory...
Experimental innovations starting in the 1990’s leading to the advent of high-throughput experiments...
Reverse engineering of gene networks aims at revealing the structure of the gene regulation network ...
The quest to determine cause from effect is often referred to as reverse engineering in the context ...
The paper describes the problem of discovering genetic networks from time course gene expression dat...
International audienceBACKGROUND: Inferring gene regulatory networks from data requires the developm...
This is the final version of the article. Available from the publisher via the DOI in this record.Un...
Background The evolution of high throughput technologies that measure gene expression levels has cr...
This work appears to complement an existingproject, Bio-inpired reverse engineering of regula-tory ...
Inferring gene networks is a daunting task. We here describe several algorithms we used in the Dialo...