Abstract
The concept of “neural network” emerges by electronic models inspired to the neural structure of human brain. Neural networks aim to solve problems currently out of computer's calculation capacity, trying to mimic the role of human brain. Recently, the number of biological based applications using neural networks is growing up. Biological networks represent correlations, extracted from sets of clinical data, diseases, mutations, and patients, and many other types of clinical or biological features. Biological networks are used to model both the state of a range of functionalities in a particular moment, and the space-time distribution of biological and clinical events.The study of biological networks, their analysis and modeling are important tasks in life sciences. Most biological networks are still far from being complete and they are often difficult to interpret due to the complexity of relationships and the peculiarities of the data. Starting from preliminary notions about neural networks, we focus on biological networks and discuss some well-known applications, like protein-protein interaction networks, gene regulatory networks (DNA-protein interaction networks), metabolic networks, signaling networks, neuronal network, phylogenetic trees and special networks. Finally, we consider the use of biological network inside a proposed model to map health related data.
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