Title :
A review on evolution of data mining techniques for protein sequence causing genetic disorder diseases
Author :
Kokilam, K.V. ; Latha, D.P.M.P.
Author_Institution :
Dept. of Comput. Applic., Karunya Univ., Coimbatore, India
Abstract :
Data mining is successfully visible in fields like marketing, finance, retail and various other sectors. The biological science contains rich information but poor knowledge. There are more number of information available within the biological science. Biological data includes protein sequence, function, pathways, nucleic acid and genetic interaction. Bioinformatics is a branch of study which deals with storage, retrieval, analysis of the Biological data. However, there is a lacking in availability of analysis tools which discover relationships that are hidden and trends in data. Purpose of this paper is to reveal the mechanisms by which mutations of proteins in our bodies is also the main cause of genetic disorder. This research paper intends to provide a review of the evolution of current data mining techniques in biological databases that are in use today.
Keywords :
bioinformatics; data analysis; data mining; genetics; medical disorders; proteins; analysis tool; bioinformatics; biological database; biological science; bological data; data analysis; data mining technique evolution; data retrieval; data storage; genetic disorder disease; genetic interaction; nucleic acid; protein function; protein mutation; protein pathway; protein sequence; relationship discovery; Classification; Clustering; Data Mining; Decision Tree; Genetic Diseases;
Conference_Titel :
Computational Intelligence & Computing Research (ICCIC), 2012 IEEE International Conference on
Conference_Location :
Coimbatore
Print_ISBN :
978-1-4673-1342-1
DOI :
10.1109/ICCIC.2012.6510284
