Sequence Alignment and HMM
Biological Sequence Alignment Using Hidden Markov Method
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DNA research has been established for years. Scientists have discovered structure of DNA and protein. As an outcome of these studies, lots of living organisms DNA sequences have been discovered. In time, DNA analysis and protein analysis have become important. By the development of computer software and Artificial Intelligence, computational biology has been emerged to be a very popular discipline. Sequence alignment requires a comparison of two or more sequences. The purpose of this comparison is to observe a similarity between the sequences. The similarity indicates such structures that have...
DNA research has been established for years. Scientists have discovered structure of DNA and protein. As an outcome of these studies, lots of living organisms DNA sequences have been discovered. In time, DNA analysis and protein analysis have become important. By the development of computer software and Artificial Intelligence, computational biology has been emerged to be a very popular discipline. Sequence alignment requires a comparison of two or more sequences. The purpose of this comparison is to observe a similarity between the sequences. The similarity indicates such structures that have the same functions. In Computational Biology there are many applications of sequence alignment. It is a fact that Biological Sequence alignment is at the core of the Bioinformatics. The purpose of this book is to implement a global pairwise sequence alignment and database search using the Hidden Markov Method. Inherent to problem structure, it can be solved by Dynamic Programming. However this method poses a weakness that eventually leads to the excessive memory usage once you try all the possibilities. On the other hand, stochastic methods evaluate the results according to a model.
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