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Claudio Mattiussi

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Publications associées (37)

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Artiﬁcial neural networks, electronic circuits, and gene networks are some examples of systems that can be modeled as networks, that is, as collections of interconnected nodes. In this paper we introduce the concept of terminal graph (t-graph for short), w ...

2011

Genetic representation and evolvability of modular neural controllers

Dario Floreano, Claudio Mattiussi, Peter Dürr

The manual design of con- trol systems for robotic devices can be challenging. Methods for the automatic synthesis of control systems, such as the evolution of artificial neural networks, are thus widely used in the robotics community. However, in many rob ...

Institute of Electrical and Electronics Engineers2010

Revealing strengths and weaknesses of methods for gene network inference

Dario Floreano, Claudio Mattiussi, Daniel Marbach, Thomas Schaffter

Numerous methods have been developed for inferring gene regulatory networks from expression data, however, both their absolute and comparative performance remain poorly understood. In this paper, we introduce a framework for critical performance assessment ...

2010

Evolutionary Selection of Features for Neural Sleep/Wake Discrimination

Dario Floreano, Claudio Mattiussi, Walter Karlen, Peter Dürr, Jérémie Guignard

In biomedical signal analysis, artificial neural networks are often used for pattern classification because of their capability for nonlinear class separation and the possibility to efficiently implement them on a microcontroller. Typically, the network to ...

Hindawi Publishing Corporation2009

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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 int ...

Blackwell Publishing, 9600 Garsington Rd, Oxford Ox4 2Dq, Oxen, England2009

Combining Multiple Results of a Reverse Engineering Algorithm: Application to the DREAM Five Gene Network Challenge

Dario Floreano, Claudio Mattiussi, Daniel Marbach

The output of reverse engineering methods for biological networks is often not a single network prediction, but an ensemble of networks that are consistent with the experimentally measured data. In this paper, we consider the problem of combining the infor ...

Blackwell Publishing, 9600 Garsington Rd, Oxford Ox4 2Dq, Oxen, England2009

Generating Realistic In Silico Gene Networks for Performance Assessment of Reverse Engineering Methods

Dario Floreano, Claudio Mattiussi, Daniel Marbach, Thomas Schaffter

Reverse engineering methods are typically first tested on simulated data from in silico networks, for systematic and efficient performance assessment, before an application to real biological networks. In this paper we present a method for generating biolo ...

2009

Sleep and Wake Classification With ECG and Respiratory Effort Signals

Dario Floreano, Claudio Mattiussi, Walter Karlen

We describe a method for the online classification of sleep/wake states based on cardiorespiratory signals produced by wearable sensors. The method was conceived in view of its applicability to a wearable sleepiness monitoring device. The method uses a Fas ...

2009

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Artificial neural networks are applied to many real-world problems, ranging from pattern classification to robot control. In order to design a neural network for a particular task, the choice of an architecture (including the choice of a neuron model), and ...

2008

The Age of Analog Networks

Dario Floreano, Claudio Mattiussi, Daniel Marbach, Peter Dürr

A large class of systems of biological and technological relevance can be described as analog networks, that is, collections of dynamical devices interconnected by links of varying strength. Some examples of analog networks are genetic regulatory networks, ...

2008