DocumentCode :
2199444
Title :
Exploring Dominating Features from Apis Mellifera Pre-miRNA
Author :
Mishra, A.K. ; Lobiyal, D.K.
Author_Institution :
Sch. of Comput. & Syst. Sci., Jawaharlal Nehru Univ., New Delhi
fYear :
2008
fDate :
20-22 Dec. 2008
Firstpage :
363
Lastpage :
367
Abstract :
In this paper, we report systematic in depth analysis of 54 known pre-miRNA from Apis mellifera (honey bee) with a set of 14 attributes. We have derived this set of attributes from secondary structure data that are generated from pre-miRNA sequences from Apis meillfera database using RNAfold. Principal component analysis method has been applied for dimension reduction. It reduces dimension of this set from 54 to a set of 7. Out of these 7 only five eigenvectors with variance more than 1.0 are considered since other attributes showed a very low variance. From this reduced set most dominating attributed are identified using attributes ranking computed by using weights of attributes and variance of five eigenvectors. All attributes with rank more than 1.0 are selected. This cast the attributes set from dimension 14 to 4 dominating attributes set. These attributes can be used in pre-miRNA prediction model that may facilitate miRNA biogenesis.
Keywords :
biology computing; macromolecules; molecular biophysics; organic compounds; principal component analysis; Apis mellifera pre-miRNA database; attributes; data structure; dimension reduction; eigenvectors; honey bee; principal component analysis; Animal structures; Biological processes; Databases; Gene expression; Organisms; Plants (biology); Predictive models; Principal component analysis; RNA; Sequences; PCA; Secondary structure; Variance; miRNA; pre-miRNA;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advanced Computer Theory and Engineering, 2008. ICACTE '08. International Conference on
Conference_Location :
Phuket
Print_ISBN :
978-0-7695-3489-3
Type :
conf
DOI :
10.1109/ICACTE.2008.169
Filename :
4736982
Link To Document :
بازگشت