Screen LibraryComputational biology of cancer : lecture notes and mathematical modeling /
The book shows how mathematical and computational models can be used to study cancer biology. It introduces the concept of mathematical modeling and then applies it to a variety of topics in cancer biology. These include aspects of cancer initiation and progression, such as the somatic evolution of...
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| Main Authors: | |
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| Corporate Authors: | |
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| Published: |
World Scientific Pub. Co.,
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| Publisher Address: | Singapore ; Hackensack, N.J. : |
| Publication Dates: | 2005. |
| Literature type: | eBook |
| Language: | English |
| Subjects: | |
| Online Access: |
http://www.worldscientific.com/worldscibooks/10.1142/5642#t=toc |
| Summary: |
The book shows how mathematical and computational models can be used to study cancer biology. It introduces the concept of mathematical modeling and then applies it to a variety of topics in cancer biology. These include aspects of cancer initiation and progression, such as the somatic evolution of cells, genetic instability, and angiogenesis. The book also discusses the use of mathematical models for the analysis of therapeutic approaches such as chemotherapy, immunotherapy, and the use of oncolytic viruses. |
| Carrier Form: | 1 online resource (xiv,250pages) : illustrations |
| Bibliography: | Includes bibliographical references (pages 227-244) and index. |
| ISBN: | 9789812701367 (electronic bk.) |
| CLC: | R730 |
| Contents: | 1. Cancer and somatic evolution. 1.1. What is cancer? 1.2. Basic cancer genetics. 1.3. Multi-stage carcinogenesis and colon cancer. 1.4. Genetic instability. 1.5. Barriers to cancer progression : importance of the microenvironment. 1.6. Evolutionary theory and Darwinian selection -- 2. Mathematical modeling of tumorigenesis. 2.1. Ordinary differential equations. 2.2. Partial differential equations. 2.3. Discrete, cellular automaton models. 2.4. Stochastic modeling. 2.5. Statistics and parameter fitting. 2.6. Concluding remarks -- 3. Cancer initiation : one-hit and two-hit stochastic models. 3.1. A one-hit model. 3.2. A two-hit model. 3.3. Modeling non-constant populations. 3.4. Overview -- 4. Microsatellite and chromosomal instability in sporadic and familial cancers. 4.1. Some biological facts about genetic instability in colon cancer. 4.2. A model for the initiation of sporadic colorectal cancers. 4.3. Sporadic colorectal cancers, CIN and MSI. 4.4. FAP. 4.5. HNPCC. 4.6. Insights following from this analysis -- 5. Cellular origins of cancer. 5.1. Stem cells, tissue renewal and cancer. 5.2. The basic renewal model. 5.3. Three scenarios. 5.4. Mathematical analysis. 5.5. Implications and data -- 6. Costs and benefits of chromosomal instability. 6.1. The effect of chromosome loss on the generation of cancer. 6.2. Calculating the optimal rate of chromosome loss. 6.3. Why does CIN emerge? 6.4. The bigger picture -- 7. DNA damage and genetic instability. 7.1. Competition dynamics. 7.2. Competition dynamics and cancer evolution. 7.3. Summary of mathematical results. 7.4. Selection for genetic instability. 7.5. Genetic instability and apoptosis. 7.6. Can competition be reversed by chemotherapy? -- 8. Tissue aging and the development of cancer. 8.1. What is aging? 8.2. Basic modeling assumptions. 8.3. Modeling healthy tissue. 8.4. Modeling tumor cell growth. 8.5. Checkpoints and basic tumor growth. 8.6. Tumor growth and the microenvironment. 8.7. Theory and data -- 9. Basic models of tumor inhibition and promotion. 9.1. Model 1 : Angiogenesis inhibition induces cell death. 9.2. Model 2 : Angiogenesis inhibition prevents tumor cell division. 9.3. Spread of tumors across space. 9.4. Somatic cancer evolution and progression. 9.5. Clinical implications -- 10. Mechanisms of tumor neovascularization. 10.1. Emergence of the concept of postnatal vasculogenesis. 10.2. Relative importance of angiogenesis versus vasculogenesis. 10.3. Mathematical models of tumor angiogenesis and vasculogenesis. 10.4. Mathematical analysis. 10.5. Applications -- 11. Cancer and immune responses. 11.1. Some facts about immune responses. 11.2. The model. 11.3. Method of model analysis. 11.4. Properties of the model. 11.5. Immunity versus tolerance. 11.6. Cancer initiation. 11.7. Tumor dormancy, evolution, and progression. 11.8. Immunotherapy against cancers -- 12. Therapeutic approaches : viruses as anti-tumor weapons. 12.1. Virus-induced killing of tumor cells. 12.2. Effect of virus-specific CTL. 12.3. Virus infection and the induction of tumor-specific CTL. 12.4. Interactions between virus-and tumor-specific CTL. 12.5. Treatment strategies. 12.6. Evaluating viruses in culture. |