File Entry: Optimized Local Protein Structure with Support Vector Machine to Predict Protein Secondary Structure
Created: 2012-05-11 02:27:24
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| Title | Optimized Local Protein Structure with Support Vector Machine to Predict Protein Secondary Structure |
| File name | C.Y.Fai2011-Optimized_Local_Protein_Structure_with_Support_Vector_Machine_to_Predict_Protein_Secondary_Structure.pdf |
| File size | 2022386 |
| SHA1 | ba4f06e0410edb01e802b7fcd049173a0843d719 |
| Content type | Adobe PDF |
Description
Protein includes many substances, such as enzymes, hormones
and antibodies that are necessary for the organisms. Living cells are
controlled by proteins and genes that interact 1fo1sngh complex molecular
pathways to achieve a specific function. These proteins have different
shapes and structures which distinct them from each other. By having
unique structures, only proteins able to carried out their function efficiently.
Therefore, determination of protein structure is fundamental for the
rmderstanding of the cell's functions. The firnction of a protein is also
largely determined by its structure. The importance of understanding
protein structure has fueled the development of protein structure databases
and prediction tools. Computational methods which were able to predict
protein structure for the determination of protein function efficiently and
accurately are in high demand. In this study, local protein structure with
Support Vector Machine is proposed to predict protein secondary structure.
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