TY - GEN
T1 - Algorithms for splicing junction donor recognition in genomic DNA sequences
AU - Yin, Maisheng
AU - Wang, J. T.L.
N1 - Publisher Copyright:
© 1998 IEEE.
PY - 1998
Y1 - 1998
N2 - The consensus sequences at splicing junctions in genomic DNA are required for pre-mRNA breaking and rejoining which must be carried out precisely. Programs currently available for identification or prediction of transcribed sequences from within genomic DNA are far from being powerful enough to elucidate genomic structure completely [2]. In this research, we develop pattern matching algorithms for 5' splicing site (donor site) recognition. Using the Motif models we develop, we can mine out the degenerate pattern information from the consensus splicing junction sequences. The experimental results show that, our algorithm can correctly recognize 93% of the total donor sites at the right positions in the test DNA group. Furthermore, more than 91% of the donor sites our algorithm predicts are correct. These precision rates are higher than the best existing donor classification algorithm [12]. The research makes a very important progress toward the development of our algorithms for full gene structure detection.
AB - The consensus sequences at splicing junctions in genomic DNA are required for pre-mRNA breaking and rejoining which must be carried out precisely. Programs currently available for identification or prediction of transcribed sequences from within genomic DNA are far from being powerful enough to elucidate genomic structure completely [2]. In this research, we develop pattern matching algorithms for 5' splicing site (donor site) recognition. Using the Motif models we develop, we can mine out the degenerate pattern information from the consensus splicing junction sequences. The experimental results show that, our algorithm can correctly recognize 93% of the total donor sites at the right positions in the test DNA group. Furthermore, more than 91% of the donor sites our algorithm predicts are correct. These precision rates are higher than the best existing donor classification algorithm [12]. The research makes a very important progress toward the development of our algorithms for full gene structure detection.
UR - http://www.scopus.com/inward/record.url?scp=0006555630&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=0006555630&partnerID=8YFLogxK
U2 - 10.1109/IJSIS.1998.685439
DO - 10.1109/IJSIS.1998.685439
M3 - Conference contribution
AN - SCOPUS:0006555630
SN - 078034863X
SN - 9780780348639
T3 - Proceedings - IEEE International Joint Symposia on Intelligence and Systems
SP - 169
EP - 176
BT - Proceedings - IEEE International Joint Symposia on Intelligence and Systems
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 1998 IEEE International Joint Symposia on Intelligence and Systems
Y2 - 21 May 1998 through 23 May 1998
ER -