
Coding and functional defect region prediction of placental protein in an embryo cell of first trimester using ANN approach
Author(s) -
Bindu Nair,
Rahul Reghunath
Publication year - 2018
Publication title -
international journal of engineering and technology
Language(s) - English
Resource type - Journals
ISSN - 2227-524X
DOI - 10.14419/ijet.v7i1.9.9756
Subject(s) - coding (social sciences) , computer science , classifier (uml) , embryo , coding region , artificial intelligence , computational biology , exon , pattern recognition (psychology) , bioinformatics , biology , genetics , gene , mathematics , statistics
The protein coding and functional regions in DNA sequences has become an exciting task in bioinformatics. In particular, the coding region has a 3-base periodicity, which helps for exon identification. Many signal processing tools and techniques have been successfully applied to identify tasks, but still need to be improved in this direction. In our work, we employ ANN classifier to predict coding and functional region of proteinin human embryo cell protein in first trimester, and evaluate their performances according to the comparison energy levels of coding region. The obtained from the threshold energy level, results show that in a box plot finally predict the mutation.