Results 251 to 260 of about 1,005,916 (291)

The Human Molecular Genetics Network

New England Journal of Medicine, 1995
To the Editor: With regard to your editorial on the Internet and the Journal (June 22 issue),1 the availability of biomedical services on the Internet promises to change many aspects of contemporar...
Gambacorti-Passerini, Carlo, Ott, Jurg, Bergen, Arthur   +2 more
openaire   +1 more source

Mutation-Based Genetic Neural Network

IEEE Transactions on Neural Networks, 2005
Evolving gradient-learning artificial neural networks (ANNs) using an evolutionary algorithm (EA) is a popular approach to address the local optima and design problems of ANN. The typical approach is to combine the strength of backpropagation (BP) in weight learning and EA's capability of searching the architecture space.
Paulito P, Palmes, Taichi, Hayasaka, Shiro, Usui   +2 more
openaire   +2 more sources

Combinatorial Synthesis of Genetic Networks

Science, 2002
A central problem in biology is determining how genes interact as parts of functional networks. Creation and analysis of synthetic networks, composed of well-characterized genetic elements, provide a framework for theoretical modeling. Here, with the use of a combinatorial method, a library of networks with varying connectivity was
Călin C, Guet, Michael B, Elowitz, Weihong, Hsing, Stanislas, Leibler   +3 more
openaire   +2 more sources

Genetic Networks and Soft Computing

IEEE/ACM Transactions on Computational Biology and Bioinformatics, 2011
The analysis of gene regulatory networks provides enormous information on various fundamental cellular processes involving growth, development, hormone secretion, and cellular communication. Their extraction from available gene expression profiles is a challenging problem.
Sushmita, Mitra, Ranajit, Das, Yoichi, Hayashi   +2 more
openaire   +2 more sources

Genetic Network Models of Biodegradation

1998
The dynamical model of bacterial degradation of organic compounds which is discussed here provides a description of the degrading behaviour in terms of interacting genes which may switch from active to inactive state, thus providing a generalization of the well known Kauffman model of random boolean networks, which is well suited for single cells, to ...
SERRA, Roberto, VILLANI, Marco, Salvemini A.   +2 more
openaire   +2 more sources

Genetics moving to neuronal networks

Trends in Neurosciences, 2005
Neuronal circuits are essential components of the nervous system and determine various body functions. To understand how neuronal circuits operate it is necessary to identify the participating neuronal subpopulations and to dissect the function of the neurons at the molecular level.
openaire   +2 more sources

Genetically Trained Cellular Neural Networks

Neural Networks, 1997
Real-coded genetic algorithms on a parallel architecture are applied to optimize the synaptic couplings of a Cellular Neural Network for specific greyscale image processing tasks. Using supervised learning information in the fitness function, we propose the Genetic Algorithm as a general training method for Cellular Neural Networks.
openaire   +2 more sources

Genetic Regulatory Networks

2013
With the discovery of DNA a full understanding of the program controlling all cells1 seemed in reach, as most researchers assumed that an organism is a direct reflection of its constituent genes2.
openaire   +1 more source

Genetic testing in prostate cancer management: Considerations informing primary care

Ca-A Cancer Journal for Clinicians, 2022
Veda N Giri, Todd M Morgan, David Morris
exaly  

Identification of metabolic networks by genetic co-essentiality analysis

Nature Reviews Molecular Cell Biology, 2023
Benjamin T Jackson
exaly