The Journal of Korean Institute of Information Technology (한국정보기술학회논문지)

Korean Institute of Information Technology (한국정보기술학회)
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Co-occurrence Based Drug-disease Relationship Inference with Genes as Mediators

유전자를 중간 매개로 고려한 동시발생 기반의 약물-질병 관계 추론

  • 신상원 (가천대학교 컴퓨터공학과) ;
  • 신예은 (가천대학교 컴퓨터공학과) ;
  • 장기업 (가천대학교 IT융합공학과) ;
  • 윤영미 (가천대학교 컴퓨터공학과)
  • Received : 2018.08.28
  • Accepted : 2018.11.05
  • Published : 2018.11.30
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Abstract

Drug repositioning is to discover new uses of drugs. Text mining derives knowledge from unstructured text. We propose a method to predict new drug-disease relationships by taking into account the rate of frequency of genes simultaneously measured in disease-gene and gene-drug. Co-occurrence of drug-gene and gene-disease in the biological literature is counted and calculate the rate of the gene for each drug and disease. Weights of drug-disease relationships are calculated using the average of the rates of genes that are measured and used to measure the accuracy for each disease. In measuring drug-disease relationships, a more accurate identification of relationships was shown by measuring the frequency on a sentence and considering multiple relationships than existing method.

신약 재창출은 현재 사용되는 약물의 새로운 용도를 발견하는 방법이다. 텍스트 마이닝은 정형화되지 않은 문서로부터 의미 있는 지식을 획득하는 과정을 의미한다. 본 논문에서는 약물-유전자와 유전자-질병에서 동시에 측정된 유전자 출현 빈도의 비율을 고려하여 새로운 약물-질병 관계를 추론하는 방법을 제안한다. 생물학적 문헌으로부터 약물-유전자와 유전자-질병의 동시출현 빈도를 측정하고 각 약물과 질병에 대하여 유전자의 출현 비율을 계산한다. 약물-질병 관계의 가중치는 동시에 측정된 유전자 출현 비율의 평균을 이용하여 계산되고 이를 이용하여 각 질병의 분류 정확도를 측정한다. 약물-질병 관계를 추론하는 것에서 동시출현 빈도를 문장 단위로 측정하고 여러 관계를 고려하는 방법이 기존 방법보다 더 정확히 식별해내는 것을 보였다.

Keywords

Acknowledgement

Supported by : 한국연구재단

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