Biomaterial Database

RegnANN: Reverse Engineering Gene Networks using Artificial Neural Networks. 2011

Marco Grimaldi, and Roberto Visintainer, and Giuseppe Jurman

Fondazione Bruno Kessler, Trento, Italy. marco.grimaldi@gmail.com

RegnANN is a novel method for reverse engineering gene networks based on an ensemble of multilayer perceptrons. The algorithm builds a regressor for each gene in the network, estimating its neighborhood independently. The overall network is obtained by joining all the neighborhoods. RegnANN makes no assumptions about the nature of the relationships between the variables, potentially capturing high-order and non linear dependencies between expression patterns. The evaluation focuses on synthetic data mimicking plausible submodules of larger networks and on biological data consisting of submodules of Escherichia coli. We consider Barabasi and Erdös-Rényi topologies together with two methods for data generation. We verify the effect of factors such as network size and amount of data to the accuracy of the inference algorithm. The accuracy scores obtained with RegnANN is methodically compared with the performance of three reference algorithms: ARACNE, CLR and KELLER. Our evaluation indicates that RegnANN compares favorably with the inference methods tested. The robustness of RegnANN, its ability to discover second order correlations and the agreement between results obtained with this new methods on both synthetic and biological data are promising and they stimulate its application to a wider range of problems.

UI	MeSH Term	Description	Entries
D004926	Escherichia coli	A species of gram-negative, facultatively anaerobic, rod-shaped bacteria (GRAM-NEGATIVE FACULTATIVELY ANAEROBIC RODS) commonly found in the lower part of the intestine of warm-blooded animals. It is usually nonpathogenic, but some strains are known to produce DIARRHEA and pyogenic infections. Pathogenic strains (virotypes) are classified by their specific pathogenic mechanisms such as toxins (ENTEROTOXIGENIC ESCHERICHIA COLI), etc.	Alkalescens-Dispar Group,Bacillus coli,Bacterium coli,Bacterium coli commune,Diffusely Adherent Escherichia coli,E coli,EAggEC,Enteroaggregative Escherichia coli,Enterococcus coli,Diffusely Adherent E. coli,Enteroaggregative E. coli,Enteroinvasive E. coli,Enteroinvasive Escherichia coli
D016571	Neural Networks, Computer	A computer architecture, implementable in either hardware or software, modeled after biological neural networks. Like the biological system in which the processing capability is a result of the interconnection strengths between arrays of nonlinear processing nodes, computerized neural networks, often called perceptrons or multilayer connectionist models, consist of neuron-like units. A homogeneous group of units makes up a layer. These networks are good at pattern recognition. They are adaptive, performing tasks by example, and thus are better for decision-making than are linear learning machines or cluster analysis. They do not require explicit programming.	Computational Neural Networks,Connectionist Models,Models, Neural Network,Neural Network Models,Neural Networks (Computer),Perceptrons,Computational Neural Network,Computer Neural Network,Computer Neural Networks,Connectionist Model,Model, Connectionist,Model, Neural Network,Models, Connectionist,Network Model, Neural,Network Models, Neural,Network, Computational Neural,Network, Computer Neural,Network, Neural (Computer),Networks, Computational Neural,Networks, Computer Neural,Networks, Neural (Computer),Neural Network (Computer),Neural Network Model,Neural Network, Computational,Neural Network, Computer,Neural Networks, Computational,Perceptron
D053263	Gene Regulatory Networks	Interacting DNA-encoded regulatory subsystems in the GENOME that coordinate input from activator and repressor TRANSCRIPTION FACTORS during development, cell differentiation, or in response to environmental cues. The networks function to ultimately specify expression of particular sets of GENES for specific conditions, times, or locations.	Gene Circuits,Gene Modules,Gene Networks,Transcriptional Networks,Gene Module,Circuit, Gene,Circuits, Gene,Gene Circuit,Gene Network,Gene Regulatory Network,Module, Gene,Modules, Gene,Network, Gene,Network, Gene Regulatory,Network, Transcriptional,Networks, Gene,Networks, Gene Regulatory,Networks, Transcriptional,Regulatory Network, Gene,Regulatory Networks, Gene,Transcriptional Network