Transmembrane helix prediction using feed-forward neural network

Transmembrane helix prediction using feed-forward neural network

Neural network is one of the successful methods for protein secondary structure prediction. Day to day this technology is modified, improved, even other methods also combined with it to get better result. In this paper we trained feed-forward neural network with trans-membrane protein for helix pred...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Hauptverfasser: Mottalib, M. A., Mahdi, Md. Safiur Rahman, Haque, A.B.M. Zunaid, Al Mamun, S.M., Al Mamun, Hawlader Abdullah
Format: Tagungsbericht
Sprache:eng
Schlagworte:
a-helix
Amino acids
Bioinformatics
Biological neural networks
Biology computing
Biomembranes
feed-forward neural network
Feedforward neural networks
Feedforward systems
Information technology
Neural networks
Proteins
transmembrane protein
Online-Zugang:Volltext bestellen
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Neural network is one of the successful methods for protein secondary structure prediction. Day to day this technology is modified, improved, even other methods also combined with it to get better result. In this paper we trained feed-forward neural network with trans-membrane protein for helix prediction. Using Java object oriented neural engine (JOONE) our achieved accuracy is 71%. This paper is expected to benefit researchers in proteomics by presenting a summary of developments of neural network in this area.
DOI:10.1109/ICCIT.2009.5407307