An ANFIS approach to transmembrane protein prediction

Hassan B. Kazemian, Syed A. Yusuf

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper is concerned with transmembrane prediction analysis. Most of novel drug design requires the use of Membrane proteins. Transmembrane protein structure allows pharmaceutical industry to design new drugs based on structural layout. However, laboratory experimental structure determination by X-ray crystallography is difficult to be achieved as the hydrophobic molecules do not crystalize easily. Moreover, the sheer number of proteins demands a computational solution to transmembrane regions identifications. This research therefore presents a novel Adaptive Neural Fuzzy Inference System (ANFIS) approach to predict and analyze of membrane helices in amino acid sequences. The ANFIS technique is implemented to predict membrane helices using sliding window data capturing. The paper uses hydrophobicity and propensity to encode the datasets using the conventional one letter symbol of amino acid residues. The computer simulation results show that the offered ANFIS methodology predicts transmembrane regions with high accuracy for randomly selected proteins.

Original languageEnglish
Title of host publicationProceedings of the 2014 IEEE International Conference on Fuzzy Systems, FUZZ-IEEE
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages6
ISBN (Electronic)978-1479920723
Publication statusPublished - 4 Sept 2014
Event2014 IEEE International Conference on Fuzzy Systems - Beijing, China
Duration: 6 Jul 201411 Jul 2014


Conference2014 IEEE International Conference on Fuzzy Systems
Abbreviated titleFUZZ-IEEE 2014


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