Intelligent computation applied to the study of hemoglobin variants / Computação inteligente no estudo de variantes de hemoglobina

AUTOR(ES)
DATA DE PUBLICAÇÃO

2004

RESUMO

In vitro evolution is a laboratorial method developed to molecule evolution mainly proteins. By producing mutations, this method looks for new molecule properties, aiming achieve new proteins for the development of drugs for diseases. The great challenge of in vitro evolution is the development of the highest possible number of molecules that reaches desired properties. This objective is a great challenge to be transposed, since only one infinitesimal fraction of generated proteins using DNA sequencies is usefull to obtain molecules with the desired function. Besides high financial support and time are required to apply this technique. With the objective of evaluating computacionaly and functionality of proteins mutants starting from aminoacids sequences looking for to reduce the cost and the time loosened at laboratory, this work proposes the use of intelligent computation techniques based on learning of it conspires and evolutionary computation. On the other hand, when machine learning techniques are used, it is fundamental to access data mining with high number of information. In order to reduce these difficulties, this work proposes a machine learning (ML) based on approach to evaluate computationaly hemoglobin variants. ML techniques require, in general, large data base. In order to supply this requirement, hemoglobin variants were used because there is a large number of hemoglobin variants available in the literature. The obtained results shown that is possible to develop efficient algorithms to determine hemoglobin variant function. These results can contribute for development of molecule evolution techniques

ASSUNTO(S)

hemoglobina hemoglobin seqüências mutantes mutant sequences machine learning aprendizado de máquina

ACESSO AO ARTIGO

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