Book chapter
Clustering Algorithms for ITS Sequence Data with Alignment Metrics
Proceedings of the 19th Advances in Artificial Intelligence Joint Conference, pp.1027-1031
Advances in Artificial Intelligence (AI) Joint Conference, 19th (Hobart, Australia, 04-Dec-2006–08-Dec-2006)
Lecture Notes in Computer Science (LNCS), 4304, Springer Verlag
2006
Abstract
The article describes two new clustering algorithms for DNA nucleotide sequences, summarizes the results of experimental analysis of performance of these algorithms for an ITS-sequence data set, and compares the results withknown biologically significant clusters of this data set. It is shown that both algorithms are efficient and can be used in practice.
Details
- Title
- Clustering Algorithms for ITS Sequence Data with Alignment Metrics
- Authors
- A Kelarvey (Author) - University of TasmaniaB Kang (Author) - University of TasmaniaDorothy A Steane (Author) - University of Tasmania
- Contributors
- A Sattar (Editor)B-H Kang (Editor)
- Publication details
- Proceedings of the 19th Advances in Artificial Intelligence Joint Conference, pp.1027-1031
- Conference details
- Advances in Artificial Intelligence (AI) Joint Conference, 19th (Hobart, Australia, 04-Dec-2006–08-Dec-2006)
- Series
- Lecture Notes in Computer Science (LNCS); 4304
- Publisher
- Springer Verlag
- Date published
- 2006
- DOI
- 10.1007/11941439_116
- ISSN
- 0302-9743
- ISBN
- 9783540497875
- Organisation Unit
- University of the Sunshine Coast, Queensland
- Language
- English
- Record Identifier
- 99450044002621
- Output Type
- Book chapter
Metrics
5 File views/ downloads
306 Record Views