File Download
There are no files associated with this item.
Links for fulltext
(May Require Subscription)
- Publisher Website: 10.1007/978-3-540-28651-6_11
- Scopus: eid_2-s2.0-35048857978
- Find via
Supplementary
-
Citations:
- Scopus: 0
- Appears in Collections:
Conference Paper: Unsupervised dense regions discovery in DNA microarray data
| Title | Unsupervised dense regions discovery in DNA microarray data |
|---|---|
| Authors | |
| Issue Date | 2004 |
| Publisher | Springer. |
| Citation | 5th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2004), Exeter, UK, 25-27 August 2004. In Intelligent Data Engineering and Automated Learning – IDEAL 2004: 5th International Conference, Exeter, UK. August 25-27, 2004: Proceedings, 2004, p. 71-77 How to Cite? |
| Abstract | In this paper, we introduce the notion of dense regions in DNA microarray data and present algorithms for discovering them. We demonstrate that dense regions are of statistical and biological significance through experiments. A dataset containing gene expression levels of 23 primate brain samples is employed to test our algorithms. Subsets of potential genes distinguishing between species and a subset of samples with potential abnormalities are identified. © Springer-Verlag Berlin Heidelberg 2004. |
| Persistent Identifier | http://hdl.handle.net/10722/276815 |
| ISBN | |
| ISSN | 2023 SCImago Journal Rankings: 0.606 |
| Series/Report no. | Lecture Notes in Computer Science ; 3177 |
| DC Field | Value | Language |
|---|---|---|
| dc.contributor.author | Yip, Andy M. | - |
| dc.contributor.author | Wu, Edmond H. | - |
| dc.contributor.author | Ng, Michael K. | - |
| dc.contributor.author | Chan, Tony F. | - |
| dc.date.accessioned | 2019-09-18T08:34:44Z | - |
| dc.date.available | 2019-09-18T08:34:44Z | - |
| dc.date.issued | 2004 | - |
| dc.identifier.citation | 5th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2004), Exeter, UK, 25-27 August 2004. In Intelligent Data Engineering and Automated Learning – IDEAL 2004: 5th International Conference, Exeter, UK. August 25-27, 2004: Proceedings, 2004, p. 71-77 | - |
| dc.identifier.isbn | 9783540228813 | - |
| dc.identifier.issn | 0302-9743 | - |
| dc.identifier.uri | http://hdl.handle.net/10722/276815 | - |
| dc.description.abstract | In this paper, we introduce the notion of dense regions in DNA microarray data and present algorithms for discovering them. We demonstrate that dense regions are of statistical and biological significance through experiments. A dataset containing gene expression levels of 23 primate brain samples is employed to test our algorithms. Subsets of potential genes distinguishing between species and a subset of samples with potential abnormalities are identified. © Springer-Verlag Berlin Heidelberg 2004. | - |
| dc.language | eng | - |
| dc.publisher | Springer. | - |
| dc.relation.ispartof | Intelligent Data Engineering and Automated Learning – IDEAL 2004: 5th International Conference, Exeter, UK. August 25-27, 2004: Proceedings | - |
| dc.relation.ispartofseries | Lecture Notes in Computer Science ; 3177 | - |
| dc.title | Unsupervised dense regions discovery in DNA microarray data | - |
| dc.type | Conference_Paper | - |
| dc.description.nature | link_to_subscribed_fulltext | - |
| dc.identifier.doi | 10.1007/978-3-540-28651-6_11 | - |
| dc.identifier.scopus | eid_2-s2.0-35048857978 | - |
| dc.identifier.spage | 71 | - |
| dc.identifier.epage | 77 | - |
| dc.identifier.eissn | 1611-3349 | - |
| dc.publisher.place | Berlin | - |
| dc.identifier.issnl | 0302-9743 | - |