Optimized local protein structure with support vector machine to predict protein secondary structure

Yin Fai Chin, Rohayanti Hassan, Mohd Saberi Mohamad

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

2 Citations (Scopus)


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 through 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 understanding of the cell's functions. The function 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.

Original languageEnglish
Title of host publicationKnowledge Technology - Third Knowledge Technology Week, KTW 2011, Revised Selected Papers
Number of pages10
Publication statusPublished - 2012
Externally publishedYes
Event3rd Knowledge Technology Week, KTW 2011 - Kajang, Malaysia
Duration: Jul 18 2011Jul 22 2011

Publication series

NameCommunications in Computer and Information Science
Volume295 CCIS
ISSN (Print)1865-0929


Conference3rd Knowledge Technology Week, KTW 2011


  • Local Protein Structure
  • Protein Secondary Structure Prediction
  • Support Vector Machine

ASJC Scopus subject areas

  • General Computer Science
  • General Mathematics


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