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Biochemical Parameters Based Structural Classification of HIV Proteins


Affiliations
1 Department of Bioinformatics, MANIT, Bhopal-462051, India
2 Department of Mathematics, MANIT, Bhopal-462051, India
     

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Solution NMR spectroscopy, X-ray crystallography, fiber diffraction, neutron diffraction are the fundamental structure determination methods in the development of many scientific fields. The methods also revealed the structure and functioning of many biological molecules, including vitamins, drugs, proteins and nucleic acids such as DNA. X-ray crystallography is still the chief method for characterizing the atomic structure of new materials and in discerning materials that appear similar by other experiments. Looking towards the importance of the structure determination methods the HIV enzyme secondary structures is taken to classify and predict on the basis of their biochemical and physicochemical methods like resolution, Ph, temperature, number of non hydrogen atoms and other parameters by machine learning techniques. Machine learning techniques are fast and economical and predict better results of classification and prediction. The accuracies of all the predicted parameters are predicted as 96.5217%.

Keywords

Accuracy, Classification, Prediction Resolution, Temperature.
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  • Biochemical Parameters Based Structural Classification of HIV Proteins

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Authors

Anubha Dubey
Department of Bioinformatics, MANIT, Bhopal-462051, India
Usha Chouhan
Department of Mathematics, MANIT, Bhopal-462051, India

Abstract


Solution NMR spectroscopy, X-ray crystallography, fiber diffraction, neutron diffraction are the fundamental structure determination methods in the development of many scientific fields. The methods also revealed the structure and functioning of many biological molecules, including vitamins, drugs, proteins and nucleic acids such as DNA. X-ray crystallography is still the chief method for characterizing the atomic structure of new materials and in discerning materials that appear similar by other experiments. Looking towards the importance of the structure determination methods the HIV enzyme secondary structures is taken to classify and predict on the basis of their biochemical and physicochemical methods like resolution, Ph, temperature, number of non hydrogen atoms and other parameters by machine learning techniques. Machine learning techniques are fast and economical and predict better results of classification and prediction. The accuracies of all the predicted parameters are predicted as 96.5217%.

Keywords


Accuracy, Classification, Prediction Resolution, Temperature.