Reducing The Search Space And Time Complexity Of Needleman Wunsch Algorithm Global Alignment And Smith Waterman Algorithm Local Algorithm For Dna Sequence Alignment
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Reducing the Search Space and Time Complexity of Needleman-Wunsch Algorithm (Global Alignment) and Smith-Waterman Algorithm (Local Algorithm) for DNA Sequence Alignment
The main research in this project is to align the DNA sequences by using the Needleman-Wunsch algorithm for global alignment and Smith-Waterman algorithm for local alignment based on the Dynamic Programming algorithm.
Machine Learning and Data Mining in Pattern Recognition
This book constitutes the refereed proceedings of the 12th International Conference on Machine Learning and Data Mining in Pattern Recognition, MLDM 2016, held in New York, NY, USA in July 2016. The 58 regular papers presented in this book were carefully reviewed and selected from 169 submissions. The topics range from theoretical topics for classification, clustering, association rule and pattern mining to specific data mining methods for the different multimedia data types such as image mining, text mining, video mining and Web mining.