논문 상세보기
pp.37-44
In this study, chemicals with acute toxicity experimental data were selected as research subjects, and compareed the model derived from statistical analysis and QSAR open-source programs. The physical and chemical properties, dynamic behaviors, and toxicological estimates of the chemicals were calculated using Mordred, a molecular descriptor calculation program based on RDKit. LD50 was set as the toxicity comparison target for each chemical, and independent variables or factors with similarity to independent variables were estimated from the molecular descriptors calculated through Mordred. Molecule descriptors composed of independent variables were compared to predictions from QSAR open-source models, A regression model was created with the selected molecule descriptors and compared with predictions from QSAR programs, confirming high accuracy for specific functional groups. The QSAR model created in this study considers the characteristics and experimental values of each chemical, and provides evidence for selecting variables when constructing toxicity data for machine learning applications.
1. 서 론
2. 연구방법
2.1 연구절차
2.2 유해성 지표 선정
2.3 데이터 세트 설정
2.4 소프트웨어 선정
2.5 분석방법
2.6 회귀모델 성능 검증
3. 연구결과
3.1 변수 간 상관분석 결과
3.2 회귀분석 결과 및 회귀모델 생성
3.3 QSAR 기반 회귀모델 성능 검증
4. 고찰 및 결론
5. References
저자 소개
