Department of Computer Science

Permanent URI for this collection

Now showing 1 - 1 of 1

A novel modeling in mathematical biology for classification of signal peptides
(Scientific Reports, 2018) Asma Ehsan; Khalid Mahmood; Yaser Daanial Khan; Sher Afzal Khan; Chou, Kuo-Chen
The molecular structure of macromolecules in living cells is ambiguous unless we classify them in a scientifc manner. Signal peptides are of vital importance in determining the behavior of newly formed proteins towards their destined path in cellular and extracellular location in both eukaryotes and prokaryotes. In the present research work, a novel method is ofered to foreknow the behavior of signal peptides and determine their cleavage site. The proposed model employs neural networks using isolated sets of prokaryote and eukaryote primary sequences. Protein sequences are classifed as secretory or non-secretory in order to investigate secretory proteins and their signal peptides. In comparison with the previous prediction tools, the proposed algorithm is more rigorous, wellorganized, signifcantly appropriate and highly accurate for the examination of signal peptides even in extensive collection of protein sequences.