Abstract
Based on the general framework of logical analysis of data, we develop a probe design method for selecting short oligo probes for genotyping applications in this paper. When extensively tested on genomic sequences downloaded from the Lost Alamos National Laboratory and the National Center of Biotechnology Information websites in various monospecific and polyspecific in silico experimental settings, the proposed probe design method selected a small number of oligo probes of length 7 or 8 nucleotides that perfectly classified all unseen testing sequences. These results well illustrate the utility of the proposed method in genotyping applications.
| Original language | English |
|---|---|
| Title of host publication | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Pages | 86-97 |
| Number of pages | 12 |
| Volume | 4509 LNAI |
| Publication status | Published - 2007 Dec 24 |
| Event | 20th Conference of the Canadian Society for Computational Studies of Intelligence, CSCSI, Canadian AI 2007 - Montreal, Canada Duration: 2007 May 28 → 2007 May 30 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 4509 LNAI |
| ISSN (Print) | 03029743 |
| ISSN (Electronic) | 16113349 |
Other
| Other | 20th Conference of the Canadian Society for Computational Studies of Intelligence, CSCSI, Canadian AI 2007 |
|---|---|
| Country | Canada |
| City | Montreal |
| Period | 07/5/28 → 07/5/30 |
Fingerprint
Keywords
- LAD
- Learning theory
- Microarrays
- Oligo probes
- Optimization
- Set covering
- Viral pathogens
ASJC Scopus subject areas
- Computer Science(all)
- Biochemistry, Genetics and Molecular Biology(all)
- Theoretical Computer Science
Cite this
Selecting genotyping oligo probes via logical analysis of data. / Kim, Kwangsoo; Ryoo, Hong Seo.
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics). Vol. 4509 LNAI 2007. p. 86-97 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 4509 LNAI).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Selecting genotyping oligo probes via logical analysis of data
AU - Kim, Kwangsoo
AU - Ryoo, Hong Seo
PY - 2007/12/24
Y1 - 2007/12/24
N2 - Based on the general framework of logical analysis of data, we develop a probe design method for selecting short oligo probes for genotyping applications in this paper. When extensively tested on genomic sequences downloaded from the Lost Alamos National Laboratory and the National Center of Biotechnology Information websites in various monospecific and polyspecific in silico experimental settings, the proposed probe design method selected a small number of oligo probes of length 7 or 8 nucleotides that perfectly classified all unseen testing sequences. These results well illustrate the utility of the proposed method in genotyping applications.
AB - Based on the general framework of logical analysis of data, we develop a probe design method for selecting short oligo probes for genotyping applications in this paper. When extensively tested on genomic sequences downloaded from the Lost Alamos National Laboratory and the National Center of Biotechnology Information websites in various monospecific and polyspecific in silico experimental settings, the proposed probe design method selected a small number of oligo probes of length 7 or 8 nucleotides that perfectly classified all unseen testing sequences. These results well illustrate the utility of the proposed method in genotyping applications.
KW - LAD
KW - Learning theory
KW - Microarrays
KW - Oligo probes
KW - Optimization
KW - Set covering
KW - Viral pathogens
UR - http://www.scopus.com/inward/record.url?scp=37249089865&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=37249089865&partnerID=8YFLogxK
M3 - Conference contribution
AN - SCOPUS:37249089865
SN - 9783540726647
VL - 4509 LNAI
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 86
EP - 97
BT - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
ER -