TY - GEN
T1 - HAMMER algorithm
T2 - 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
AU - Sheng, Huitao
AU - Mehrotra, Kishan
AU - Mohan, Chilukuri
AU - Raina, Ramesh
PY - 2007
Y1 - 2007
N2 - A new algorithm, HAMMER, discovers cis-elements in promoter regions of the co-regulated genes. We show that HAMMER is faster and more accurate than well-known tools currently in use to identify cis-elements. Given input sequences that represent promoter regions of genes, this algorithm searches for subsequences of desired length w whose frequency of occurrence is relatively high, while accounting for slightly corrupted variants (with up to d substitutions). Various w-mers are numerically encoded and represented in a hash table, and d-neighbors are efficiently discovered using a modulo-4 arithmetic operation. Profile matrices are constructed and evaluated using a high-order Markov model based on background data (from a gene database). HAMMER discovers the most frequently occurring w-mers (permitting corruption in at most d positions). Experiment results show that HAMMER is significantly faster and discovers more motifs present in the test sequences, when compared with two well-known motif-discovery tools (MDScan and AlignACE).
AB - A new algorithm, HAMMER, discovers cis-elements in promoter regions of the co-regulated genes. We show that HAMMER is faster and more accurate than well-known tools currently in use to identify cis-elements. Given input sequences that represent promoter regions of genes, this algorithm searches for subsequences of desired length w whose frequency of occurrence is relatively high, while accounting for slightly corrupted variants (with up to d substitutions). Various w-mers are numerically encoded and represented in a hash table, and d-neighbors are efficiently discovered using a modulo-4 arithmetic operation. Profile matrices are constructed and evaluated using a high-order Markov model based on background data (from a gene database). HAMMER discovers the most frequently occurring w-mers (permitting corruption in at most d positions). Experiment results show that HAMMER is significantly faster and discovers more motifs present in the test sequences, when compared with two well-known motif-discovery tools (MDScan and AlignACE).
UR - http://www.scopus.com/inward/record.url?scp=47649104914&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=47649104914&partnerID=8YFLogxK
U2 - 10.1109/BIBE.2007.4375645
DO - 10.1109/BIBE.2007.4375645
M3 - Conference contribution
AN - SCOPUS:47649104914
SN - 1424415098
SN - 9781424415090
T3 - Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
SP - 753
EP - 758
BT - Proceedings of the 7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE
Y2 - 14 January 2007 through 17 January 2007
ER -