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MATLAB & Simulink을 활용한 암세포와 상호작용에서 섬유블라스트의 모델링 접근법연구(The double-edged sword role of fibroblasts in t


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MATLAB & Simulink을 활용한 암세포와 상호작용에서 섬유블라스트의 모델링 접근법연구(The double-edged sword role of fibroblasts in t

Zarifeh Heidary, Jafar Ghaisari, Shiva Moein, Shaghayegh Haghjooy Javanmard 저 | 아진

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2020-07-14
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한줄서평

콘텐츠 소개

Fibroblasts as key components of tumor microenvironment show different features
in the interaction with cancer cells. Although, Normal fibroblasts demonstrate
anti-tumor effects, cancer associated fibroblasts are principal participant in tumor
growth and invasion. The ambiguity of fibroblasts function can be regarded as two
heads of its behavioral spectrum and can be subjected for mathematical modeling
to identify their switching behavior. In this research, an agent-based model of
mutual interactions between fibroblast and cancer cell was created. The proposed
model is based on nonlinear differential equations which describes biochemical
reactions of the main factors involved in fibroblasts and cancer cells
communication. Also, most of the model parameters are estimated using hybrid
unscented Kalman filter. The interactions between two cell types are illustrated by
the dynamic modeling of TGFβ and LIF pathways as well as their crosstalk. Using
analytical and computational approaches, reciprocal effects of cancer cells and
fibroblasts are constructed and the role of signaling molecules in tumor progression
or prevention are determined. Finally, the model is validated using a set of
experimental data. The proposed dynamic modeling might be useful for designing
more efficient therapies in cancer metastasis treatment and prevention.

목차

제 1편 : SIMULINK 기본편
1.1 SIMULINK의 시작 1
블록의 연결 5
블록 파라미터의 설정 7
시뮬레이션 파라미터 (Configuration Parameters)의 설정 8
시뮬레이션의 수행 9
블록 파라미터의 표시 9
복수 데이터의 표시 11
2.2 동적 시뮬레이션 13
이차 미분방정식 17
선형 상태변수 모델 23
DC 모터의 시뮬레이션 24
함수 블록의 사용 29
차분방정식(difference equation)의 모델링 34
Subsystem(부시스템)의 구성 37
제 2편 : 연구논문
The double-edged sword role of fibroblasts in the interaction with
cancer cells; an agentbased modeling approach
1. Introduction 41
2. Materials and methods 43
3. Model parameter estimation 46
4. Results 48
5. Discussion 49
6. References 51

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