Lossless Differential Compression Algorithm
This book describes algorithm for genomic data which compresses the data set based on comparing it with a reference
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The goal of this book is to develop compression algorithms to solve problems of storage of huge genomic databases and updating new dataset at any time. This book will help everyone who interested in Bioinformatic field. It's easy to understand the difference compression scheme. For difference compression scheme to be appropriate, it should be suitable for the way the set is being used. First, when an entire set is archived or transmitted, the concern will be focused on the compression rate. In this situation, a reference sequence is stored, and the next sequence is generated from this referenc...
The goal of this book is to develop compression algorithms to solve problems of storage of huge genomic databases and updating new dataset at any time. This book will help everyone who interested in Bioinformatic field. It's easy to understand the difference compression scheme. For difference compression scheme to be appropriate, it should be suitable for the way the set is being used. First, when an entire set is archived or transmitted, the concern will be focused on the compression rate. In this situation, a reference sequence is stored, and the next sequence is generated from this reference and the appropriate difference sequence. Newly generated sequences may be used as references for subsequent sequences. The second situation is when the set is being actively used, in addition to the compression rate; the speed of decompression is of comparable importance, where any sequence may be repeatedly fetched at any moment. To speed up sequence decompression, it is preferable to have a single reference for the whole set. Therefore, any generated sequence immediately generated in terms of the single reference. I hope to enjoy it.
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