Earticle

현재 위치 Home

Oral Session II - III : Emerging Topics in AI

Identification of Parkinson’s Disease-Specific Factor in the 3’ Untranslated Region with DNA Methylation Changes Using Machine Learning

첫 페이지 보기
  • 발행기관
    한국차세대컴퓨팅학회 바로가기
  • 간행물
    한국차세대컴퓨팅학회 학술대회 바로가기
  • 통권
    The 10th International Conference on Next Generation Computing 2024 (2024.11)바로가기
  • 페이지
    pp.372-374
  • 저자
    Dongjin Oh, Yedam Park, Hamin Im, Chan-Uk Yeom, Keun-Chang Kwak
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A468888

원문정보

초록

영어
Parkinson’s Disease (PD) patients were reported to exceed approximately 10 million worldwide, and the number has been consistently increasing every year. Factors causing PD are genetic and environmental factors. We focus on the effects of environmental factors on epigenetic. Specifically, the α- synuclein (SNCA) gene is a risk factor causing PD, and we analyze it based on its regulation by the methylated 3’ Untranslated Region (UTR). The analysis data consists of Deoxyribonucleic Acid (DNA) methylation by NCBI GEO datasets, including 40 samples from PD cases and 38 from cognitively healthy subjects. The total number of CpG islands (CGI) is 863,159. To select the distinctive CGI from the DNA methylation data, we apply the Recursive Feature Elimination (RFE) method. Consequently, we have the results from selecting the 20 CGIs. Based on 20 CGI, we employ four models, Support Vector Machine (SVM), RandomForest (RF), Extreme Gradient Boosting (XGBoost), and Neural Network (NN), to divide the control and PD. Among the results, the RF model achieved the highest accuracy at 87.5%. Our findings indicate that changes in DNA methylation levels of the 20 selected CGIs are associated with PD occurrence. Based on these results, we suggest that PD occurrence is related to environmental factors such as chemical stress, eating habits, and general stress. Furthermore, our paper provides insights into the relationship between epigenetics and neurodegenerative disease.

목차

Abstract
I. INTRODUCTION
II. METHOD AND MATERIAL
A. Work Flow
B. Model Description
III. RESULT
A. Data
B. Selected the CGI Group
C. Test
IV. CONCLUSION
ACKNOWLEDGMENT
REFERENCES

키워드

Parkinson’s disease DNA methylation Epigenetics 3’UTR

저자

  • Dongjin Oh [ dept. of Biomedical Science Chosun University Gwangju, Republic of Korea ]
  • Yedam Park [ dept. of Biomedical Science Chosun University Gwangju, Republic of Korea ]
  • Hamin Im [ dept. of Biomedical Science Chosun University Gwangju, Republic of Korea ]
  • Chan-Uk Yeom [ Division of AI Convergence College Chosun University Gwangju, Republic of Korea ]
  • Keun-Chang Kwak [ dept. of Electronics Engineering Chosun University Gwangju, Republic of Korea ] Corresponding Author

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    한국차세대컴퓨팅학회 [Korean Institute of Next Generation Computing]
  • 설립연도
    2005
  • 분야
    공학>컴퓨터학
  • 소개
    본 학회는 차세대 PC 및 그 관련분야의 학술활동을 통하여 차세대 PC의 학문 및 기술발전을 도모하고 산업발전 및 국제협력 증진을 목적으로 한다.

간행물

  • 간행물명
    한국차세대컴퓨팅학회 학술대회
  • 간기
    반년간
  • 수록기간
    2021~2025
  • 십진분류
    KDC 566 DDC 004

이 권호 내 다른 논문 / 한국차세대컴퓨팅학회 학술대회 The 10th International Conference on Next Generation Computing 2024

    피인용수 : 0건 (자료제공 : 네이버학술정보)

    함께 이용한 논문 이 논문을 다운로드한 분들이 이용한 다른 논문입니다.

      출처 : 네이버학술정보

        0개의 논문이 장바구니에 담겼습니다.

        페이지 저장
        소속기관 조회
        이용자님의 소속기관(단체)이 서비스에 가입되어 있는지 확인해 보십시오.
        기관회원에 소속되어 있는 이용자는 원문을 무료로 이용할 수 있습니다.