Sequence data mining
"Understanding sequence data, and the ability to utilize this hidden knowledge, creates a significant impact on many aspects of our society. Examples of sequence data include DNA, protein, customer purchase history, web surfing history, and more." "Sequence Data Mining provides balanc...
| Main Author: | Dong, Guozhu, 1957- |
|---|---|
| Other Authors: | Pei, Jian (Computer scientist), SpringerLink (Online service) |
| Format: | eBook |
| Language: | English |
| Published: |
New York :
Springer,
2007.
New York : 2007. |
| Physical Description: |
1 online resource (xv, 150 pages) : illustrations. |
| Series: |
Advances in database systems ;
v. 33. |
| Subjects: |
| Summary: |
"Understanding sequence data, and the ability to utilize this hidden knowledge, creates a significant impact on many aspects of our society. Examples of sequence data include DNA, protein, customer purchase history, web surfing history, and more." "Sequence Data Mining provides balanced coverage of the existing results on sequence data mining, as well as pattern types and associated pattern mining methods. While there are several books on data mining and sequence data analysis, currently there are no books that balance both of these topics. This volume fills in the gap, allowing readers to access state-of-the-art results in one place." "Sequence Data Mining is designed for professionals working in bioinformatics, genomics, web services, and financial data analysis. This book is also suitable for advanced-level students in computer science and bioengineering."--Jacket. |
|---|---|
| Item Description: |
Includes bibliographical references (pages 139-146) and index. "Understanding sequence data, and the ability to utilize this hidden knowledge, creates a significant impact on many aspects of our society. Examples of sequence data include DNA, protein, customer purchase history, web surfing history, and more." "Sequence Data Mining provides balanced coverage of the existing results on sequence data mining, as well as pattern types and associated pattern mining methods. While there are several books on data mining and sequence data analysis, currently there are no books that balance both of these topics. This volume fills in the gap, allowing readers to access state-of-the-art results in one place." "Sequence Data Mining is designed for professionals working in bioinformatics, genomics, web services, and financial data analysis. This book is also suitable for advanced-level students in computer science and bioengineering."--Jacket. Front Matter; Introduction; Frequent and Closed Sequence Patterns; Classification, Clustering, Features and Distances of Sequence Data; Sequence Motifs: Identifying and Characterizing Sequence Families; Mining Partial Orders from Sequences; Distinguishing Sequence Patterns; Related Topics. |
| Physical Description: |
1 online resource (xv, 150 pages) : illustrations. |
| Bibliography: |
Includes bibliographical references (pages 139-146) and index. |
| ISBN: |
9780387699370 0387699376 9780387699363 0387699368 |