Title page for etd-0906111-094417


[Back to Results | New Search]

URN etd-0906111-094417
Author Zih-Jie Yang
Author's Email Address m983040064@student.nsysu.edu.tw
Statistics This thesis had been viewed 5537 times. Download 1679 times.
Department Computer Science and Engineering
Year 2011
Semester 1
Degree Master
Type of Document
Language English
Title Prediction for the Essential Protein with the Support Vector Machine
Date of Defense 2011-08-31
Page Count 67
Keyword
  • bioinformatics
  • essential protein
  • protein-protein interaction
  • support vector machine
  • feature set
  • Abstract Essential proteins affect the cellular life deeply, but it is hard to identify them. Protein-protein interaction is one of the ways to disclose whether a protein is essential or not. We notice that many researchers use the feature set composed of topology properties from protein-protein interaction to predict the essential proteins. However, the functionality of a protein is also a clue to determine its essentiality. In this thesis, to build SVM models for predicting the essential proteins, our feature set contains the sequence properties which can influence the protein function, topology properties and protein properties. In our experiments, we download Scere20070107, which contains 4873 proteins and 17166 interactions, from DIP database. The ratio of essential proteins to nonessential proteins is nearly 1:4, so it is imbalanced. In the imbalanced dataset, the best values of F-measure, MCC, AIC and BIC of our models are 0.5197, 0.4671, 0.2428 and 0.2543, respectively. We build another balanced dataset with ratio 1:1. For balanced dataset, the best values of F-measure, MCC, AIC and BIC of our models are 0.7742, 0.5484, 0.3603 and 0.3828, respectively. Our results are superior to all previous results with various measurements.
    Advisory Committee
  • Jen-Sen Lin - chair
  • Yung-Hsing Peng - co-chair
  • Yow-Ling Shiue - co-chair
  • Chang-Biau Yang - advisor
  • Files
  • etd-0906111-094417.pdf
  • Indicate in-campus at 0 year and off-campus access at 1 year.
    Date of Submission 2011-09-06

    [Back to Results | New Search]


    Browse | Search All Available ETDs

    If you have more questions or technical problems, please contact eThesys