Repository logo
Communities & Collections
All of DSpace
  • English
  • العربية
  • বাংলা
  • Català
  • Čeština
  • Deutsch
  • Ελληνικά
  • Español
  • Suomi
  • Français
  • Gàidhlig
  • हिंदी
  • Magyar
  • Italiano
  • Қазақ
  • Latviešu
  • Nederlands
  • Polski
  • Português
  • Português do Brasil
  • Srpski (lat)
  • Српски
  • Svenska
  • Türkçe
  • Yкраї́нська
  • Tiếng Việt
Log In
New user? Click here to register.Have you forgotten your password?
  1. Home
  2. Browse by Author

Browsing by Author "Harmain Asghar"

Filter results by typing the first few letters
Now showing 1 - 1 of 1
  • Results Per Page
  • Sort Options
  • No Thumbnail Available
    Item
    Computational Technique For Classification Of Membrane Proteins
    (Library Information Services, COMSATS University Islamabad, Lahore Campus, 2020) Harmain Asghar; SP18-RCS-012; LHR TP 5985; Dr. Zeeshan Gillani
    The Cell is the most important part of the human body, many small entities and molecules are encapsulated within a cell; shielded by the cell membrane. Proteins are the basic elements within the cell that are responsible for various functionalities, like nutrients across membrane and molecule, identification of foreign bodies, etc. Membrane proteins play a very important function in predicting diseases. Due to advancements in the Next-generation Sequencing, membrane proteins dataset is ever increasing. The experimental methods for the classification of these proteins are very expensive and time-consuming. In this study, prediction about the membrane proteins and its subtypes will be made based on a computational approach using protein primary sequence and machine learning algorithm. For the purpose of more improvement we used the convolutional neural network inception v3 model. The results exhibit the effectiveness of predictive performance as compared to the other existing algorithm. Some useful techniques are described to make the study more effective.

DSpace software copyright © 2002-2026 LYRASIS

  • Privacy policy
  • End User Agreement
  • Send Feedback
Repository logo COAR Notify