title: A Treatise to Computational Approaches Towards Prediction of Membrane Protein and Its Subtypes.
abstract: Membrane proteins are vital mediating molecules responsible for the interaction of a cell with its surroundings. These proteins are involved in different functionalities such as ferrying of molecules and nutrients across membrane, recognizing foreign bodies, receiving outside signals and translating them into the cell. Membrane proteins play significant role in drug interaction as nearly 50% of the drug targets are membrane proteins. Due to the momentous role of membrane protein in cell activity, computational models able to predict membrane protein with accurate measures bears indispensable importance. The conventional experimental methods used for annotating membrane proteins are time-consuming and costly and in some cases impossible. Computationally intelligent techniques have emerged to be as a useful resource in the automation of prediction and hence the annotation process. In this study, various techniques have been reviewed that are based on different computational intelligence models used for prediction process. These techniques were formulated by different researchers and were further evaluated to provide a comparative analysis. Analysis shows that the usage of support vector machine-based prediction techniques bears more assiduous results.
authors.affiliation: Department of Computer Science, School of Systems and Technology, University of Management and Technology, C-II, Johar Town, P.O. Box 10033, Lahore, 54770, Pakistan. ahmad.hassan@umt.edu.pk.
authors.forename: Ahmad Hassan
authors.initials: AH
authors.lastname: Butt
authors.affiliation: Department of Chemistry, School of Science, University of Management and Technology, C-II, Johar Town, P.O. Box 10033, Lahore, 54770, Pakistan.
authors.forename: Nouman
authors.initials: N
authors.lastname: Rasool
authors.affiliation: Department of Computer Science, School of Systems and Technology, University of Management and Technology, C-II, Johar Town, P.O. Box 10033, Lahore, 54770, Pakistan.
authors.forename: Yaser Daanial
authors.initials: YD
authors.lastname: Khan
mesh_terms: D000465:Algorithms; D000596:Amino Acids / Q000737:chemistry*; D019295:Computational Biology / Q000379:methods*; D057927:Hydrophobic and Hydrophilic Interactions; D008565:Membrane Proteins / Q000737:chemistry* / Q000145:classification*; D016571:Neural Networks, Computer; D056510:Position-Specific Scoring Matrices; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D060388:Support Vector Machine
chemical_list: D000596:Amino Acids; D008565:Membrane Proteins
keywords: Amino acids; Membrane proteins; Position-specific scoring matrix; Probabilistic neural networks; Pseudo amino acids compositions; Support vector machine