• DocumentCode
    2714602
  • Title

    Important numerical features for novel endoplasmic reticulum genes classification of protein localizations in micrographs

  • Author

    Dan, Han-Wei ; Lin, Chung-Chih ; Tsai, Yuh-Show

  • Author_Institution
    Dept. of Biomed. Eng., Chung Yuan Christian Univ., Jhongli, Taiwan
  • fYear
    2011
  • fDate
    3-5 Nov. 2011
  • Firstpage
    178
  • Lastpage
    181
  • Abstract
    Localization of proteins ties closely with the protein functions-the disorder of protein delivering can cause misfunction of the protein and genetic diseases. The analysis of micrographs can help to understand the distribution of proteins in the cell. ER protein´s images analysis leads the researches to know that the same protein localization means the proteins have same function, and to understand the phylogenetic relationship by image´s morphologies. This research uses SDA to find the best combination of features from original, skeletonized and brighter area images, which then utilized in SVM classification. The accuracy of this system can achieve 74% for the images acquired by the same hardware equipment.
  • Keywords
    biomedical optical imaging; cellular biophysics; diseases; feature extraction; genetics; image classification; medical image processing; molecular biophysics; support vector machines; SDA; SVM classification; brighter area images; endoplasmic reticulum gene classification; feature extraction; genetic diseases; micrographs; phylogenetic relationship; protein delivery disorder; protein distribution; protein function; protein localization; skeletonized images; Accuracy; Educational institutions; Erbium; Feature extraction; Protein engineering; Proteins; Training;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Bioelectronics and Bioinformatics (ISBB), 2011 International Symposium on
  • Conference_Location
    Suzhou
  • Print_ISBN
    978-1-4577-0076-7
  • Type

    conf

  • DOI
    10.1109/ISBB.2011.6107675
  • Filename
    6107675