TY - GEN
T1 - Using OWA operators for gene sequential pattern clustering
AU - Nin, J.
AU - Salle, Paola
AU - Bringay, Sandra
AU - Teisseire, Maguelonne
PY - 2009
Y1 - 2009
N2 - Nowadays, the management of sequential patterns data becomes an increasing need in biological knowledge discovery processes. An important task in these processes is the restitution of the results obtained by using data mining methods. In a complex domain as biomedical, an efficient interpretation of the patterns without any assistance is difficult. One of the most common knowledge discovery proces is clustering. But the application of clustering to gene sequential patterns is far from easy on biomedical data.In this paper, we introduce a new gene sequential patterns similarity function and summarization algorithm.
AB - Nowadays, the management of sequential patterns data becomes an increasing need in biological knowledge discovery processes. An important task in these processes is the restitution of the results obtained by using data mining methods. In a complex domain as biomedical, an efficient interpretation of the patterns without any assistance is difficult. One of the most common knowledge discovery proces is clustering. But the application of clustering to gene sequential patterns is far from easy on biomedical data.In this paper, we introduce a new gene sequential patterns similarity function and summarization algorithm.
UR - http://www.scopus.com/inward/record.url?scp=70449643132&partnerID=8YFLogxK
U2 - 10.1109/CBMS.2009.5255363
DO - 10.1109/CBMS.2009.5255363
M3 - Conference contribution
AN - SCOPUS:70449643132
SN - 9781424448784
T3 - Proceedings - IEEE Symposium on Computer-Based Medical Systems
BT - 2009 22nd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2009
T2 - 2009 22nd IEEE International Symposium on Computer-Based Medical Systems, CBMS 2009
Y2 - 2 August 2009 through 5 August 2009
ER -