Title :
Estimate human gene family number by improved k-means clustering
Author :
Pu, Dongmei ; Yuan, Yubo ; Cao, Feilong
Author_Institution :
Inst. of Metrol. & Comput. Sci., China Jiliang Univ., Hangzhou, China
Abstract :
The number of gene families is a very important issue among all of genome sequencing studies. In this paper, the genome sequences has been recoded. One of it is a 64 dimensional vector. The human genome database has been recoded as a matrix which has 64 columns. After using the improved k-means clustering algorithm, the family number can be checked out and every member of each family can be determined.
Keywords :
genetics; matrix algebra; medical computing; pattern clustering; genome sequencing; human gene family number estimation; human genome database; k-means clustering; Biological cells; DNA; Humans; Silicon; clustering; data mining; human genome;
Conference_Titel :
Machine Learning and Cybernetics (ICMLC), 2010 International Conference on
Conference_Location :
Qingdao
Print_ISBN :
978-1-4244-6526-2
DOI :
10.1109/ICMLC.2010.5580732
