Chemical compounds with path frequency using multi-core technology

Kun Ming Yu*, Yi Yan Chang, Jiayi Zhou, Chun Yuan Huang, Whei Meih Chang, Chun Yuan Lin, Chuan Yi Tang

*Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Drug design is the approach of finding drugs by design using computational tools. When designing a new drug, the structure of the drug molecule can be modeled by classification of potential chemical compounds. Kernel Methods have been successfully used in classifying chemical compounds, within which the most popular one is Support Vector Machine (SVM). In order to classify the characteristics of chemical compounds, methods such as frequency of labeled paths have been proposed to map compounds into feature vectors. In this study, we analyze the path frequencies computed from chemical compounds, and reconstruct all possible compounds that share the same path frequency with the original ones, but differ in their molecular structures. Since the computation time for reconstructing such compounds increase greatly along with the size increase of the compounds, we propose an efficient algorithm based on multi-core processing technology. We report here that our algorithm can infer chemical compounds from path frequency while effectively reduce computation time and obtained high speed up.

Original languageEnglish
Title of host publicationScalable Information Systems - 4th International ICST Conference, INFOSCALE 2009, Revised Selected Papers
Pages258-271
Number of pages14
DOIs
StatePublished - 2009
Event4th International ICST Conference on Scalable Information Systems, INFOSCALE 2009 - Hong Kong, Hong Kong
Duration: 10 06 200911 06 2009

Publication series

NameLecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering
Volume18 LNICST
ISSN (Print)1867-8211

Conference

Conference4th International ICST Conference on Scalable Information Systems, INFOSCALE 2009
Country/TerritoryHong Kong
CityHong Kong
Period10/06/0911/06/09

Keywords

  • Branch-and-bound
  • Chemical compound
  • Feature space
  • Multi-core processing
  • OpenMP

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