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The idea of this work is to classify the RNA secondary structure elements using the modified backpropagation neural network. RNA secondary structure contains elements like helix, hairpin, internal loop, external loop, multi branch loop, bulge etc.The hairpin, non hairpin, helix and non helix portions are extracted using the representative and the secondary structure. Since sequences are strings of alphabets A, U, C, G and vary in length so they can t be used as such for inputs of neural network. The feature vector is extracted from sequences. Feature vector has eight parameters.

Produktbeschreibung
The idea of this work is to classify the RNA secondary structure elements using the modified backpropagation neural network. RNA secondary structure contains elements like helix, hairpin, internal loop, external loop, multi branch loop, bulge etc.The hairpin, non hairpin, helix and non helix portions are extracted using the representative and the secondary structure. Since sequences are strings of alphabets A, U, C, G and vary in length so they can t be used as such for inputs of neural network. The feature vector is extracted from sequences. Feature vector has eight parameters.
Autorenporträt
Ich bin Dr. Mangesh Mutkule und mache mein Postgraduiertenstudium in der Abteilung für Prothetik und Kronen- und Brückenbau am S.M.B.T. Dental College and Hospital, Sangamner. Unter der Leitung von Dr. Shailendra Singh (Guide) und Dr. Girish Nazirkar (Abteilungsleiter).