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Reverse Engineering and Analysis of Genome-Wide Gene Regulatory Networks from Gene Expression Profiles Using High-Performance Computing

Publications associées (102)

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Modeling of Multiple Valued Gene Regulatory Networks

Giovanni De Micheli, Abhishek Garg, Ioannis Xenarios

In silico modeling of Gene Regulatory Networks has gained a lot of attention recently as it gives a very powerful tool to experimental biologists to gather the knowledge gained from different biological experiments and understand the dynamics of the overal ...

2007

Differential gene expression as a toxicant-sensitive endpoint in zebrafish embryos and larvae

Kristin Schirmer

The zebrafish (Danio rerio) embryo toxicity test (DarT) is under consideration as an alternative to the acute fish toxicity test. Microscopically visible developmental disorders or death are the endpoints used to report on toxicity in DarT. These endpoints ...

2007

Bio-mimetic Evolutionary Reverse Engineering of Genetic Regulatory Networks

Dario Floreano, Claudio Mattiussi, Daniel Marbach

The effective reverse engineering of biochemical networks is one of the great challenges of systems biology. The contribution of this paper is two-fold: 1) We introduce a new method for reverse engineering genetic regulatory networks from gene expression d ...

Springer-Verlag Berlin2007

Experimental Design for Efficient Identification of Gene Regulatory Networks using Sparse Bayesian Models

Matthias Seeger

Background: Identifying large gene regulatory networks is an important task, while the acquisition of data through perturbation experiments (e.g., gene switches, RNAi, heterozygotes) is expensive. It is thus desirable to use an identification ...

BioMed Central2007

PPARgamma in human and mouse physiology

Johan Auwerx

The peroxisome proliferator activated receptor gamma (PPARgamma) is a member in the nuclear receptor superfamily which mediates part of the regulatory effects of dietary fatty acids on gene expression. As PPARgamma also coordinates adipocyte differentiatio ...

2007

Bayesian Inference and Optimal Design in the Sparse Linear Model

Matthias Seeger

The sparse linear model has seen many successful applications in Statistics, Machine Learning, and Computational Biology, such as identification of gene regulatory networks from micro-array expression data. Prior work has either approximated Bayesian infer ...

2007

Switch Detection in Genetic Regulatory Networks

Giancarlo Ferrari Trecate

This paper considers piecewise affine models of genetic regulatory networks and focuses on the problem of detecting switches among different modes of operation in gene expression data. This task constitutes the first step of a procedure for the complete id ...

Springer-Verlag2007

Computational Identification of MicroRNAs and Their Targets

Giovanni De Micheli

One of the most important advances in biology in recent years may be the discovery of RNAs that can regulate gene expression. As one kind of such functional noncoding RNAs, microRNAs (miRNAs) forma class of endogenous 19–23-nucleotide RNAs that can have im ...

Wiley-Blackwell2006

Bioimaging and Functional Genomics

Giovanni De Micheli, Luca Benini

For better understanding of genetic mechanisms underlying clinical observations, it is interesting to determine which genes and clinical traits are interrelated. In the last few years a consistent amount of research in genomics has been done concerning cor ...

2006

Exploiting Binary Abstractions in Deciphering Gene Interactions

Giovanni De Micheli, Abhishek Garg

We consider computationally reconstructing gene regulatory networks on top of the binary abstraction of gene expression state information. Unlike previous Boolean network approaches, the proposed method does not handle noisy gene expression values directly ...

2006