Beschreibung
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 cant be used as such for inputs of neural network. The feature vector is extracted from sequences. Feature vector has eight parameters.
Autorenporträt
Shailendra Singh is a faculty member in computer science and engineering department at PEC University of Technology, Chandigarh. His research interest includes bioinformatics, NLP and soft computing. He has received several awards and recognition in teaching and conferences. He has contributed more than 50 research papers.
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