Document Details
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Document Type |
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Article In Journal |
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Document Title |
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A Prediction Model for Membrane Proteins Using Moments Based Features A Prediction Model for Membrane Proteins Using Moments Based Features |
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Subject |
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Computer Science |
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Document Language |
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Arabic |
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Abstract |
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The most expedient unit of the human body is its cell. Encapsulated within the cell are
many infinitesimal entities and molecules which are protected by a cell membrane. The
proteins that are associated with this lipid based bilayer cell membrane are known as
membrane proteins and are considered to play a significant role. These membrane
proteins exhibit their effect in cellular activities inside and outside of the cell. According
to the scientists in pharmaceutical organizations, these membrane proteins perform key
task in drug interactions. In this study, a technique is presented that is based on various
computationally intelligent methods used for the prediction of membrane protein
without the experimental use of mass spectrometry. Statistical moments were used to
extract features and furthermore a Multilayer Neural Network was trained using
backpropagation for the prediction of membrane proteins. Results show that the
proposed technique performs better than existing methodologies. |
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ISSN |
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2314-6141 |
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Journal Name |
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BioMed Research International |
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Volume |
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2016 |
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Issue Number |
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2 |
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Publishing Year |
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1437 AH
2016 AD |
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Article Type |
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Article |
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Added Date |
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Monday, March 7, 2016 |
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Researchers
| Sher Afzal Khan | Khan, Sher Afzal | Researcher | Doctorate | skhan.afzal@gmail.com |
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