Understanding complex biological systems with mathematics. (2018)

• Record Type: Book
• Further Information: Note: Ami Radunskaya, Rebecca Segal, Blerta Shtylla, editors.
• Editors: Radunskaya, Ami; Segal, Rebecca; Shtylla, Blerta
• Contents: Intro; Women Advancing Mathematical Biology Workshop; Aim and Scope; History and Context; Research; Concluding Remarks; Acknowledgments; Contents; Searching for Superspreaders: Identifying Epidemic Patterns Associated with Superspreading Events in Stochastic Models; 1 Background; 2 Deterministic Model; 2.1 Basic Reproduction Number; 3 Markov Chain Model; 3.1 Branching Process Approximation; 4 Parameter Sensitivity Analysis; 5 CTMC Analysis; 5.1 Sample Paths; 5.2 Probability of Outbreak; 5.3 Number of Deaths; 5.4 Time to Outbreak 5.5 Time to Peak Infection and Peak Number of Infectious Individuals6 Discussion; 7 Future Work; Appendix 1: Basic Reproduction Number Calculation; Appendix 2: Expectation Matrix; Appendix 3: Latin Hypercube and Partial Rank Correlation Coefficient; References; How Disease Risks Can Impact the Evolution of Social Behaviors and Emergent Population Organization; 1 Introduction; 2 Motivation: Multilevel Selection and Social Behavior; 2.1 Review of Evolutionary Theory; 2.2 Review of Organizational Success of Static Network Structure in Populations 3 The Evolution of Emergent Population Structure from Dynamic Social Behaviors4 Disease Risks in Social Networks; 5 Extensions and Questions for Further Study; 6 Concluding Remarks; References; Mathematical Analysis of the Impact of Social Structure on Ectoparasite Load in Allogrooming Populations; 1 Introduction; 2 A Two-Compartment Model of Parasite Load; 2.1 Simplified ODE Model; 2.2 Steady-State and Bifurcation Analysis; 3 A Two-State Model of Parasite Load with Hub Nodes; 3.1 Model Formulation; 3.2 Steady-State Analysis of the Uninfected State; 4 Conclusion; References Modeling the Argasid Tick (Ornithodoros moubata) Life Cycle1 Introduction; 2 Ornithodoros moubata Biology; 3 Parameter Selection; 4 Continuous-Time Model; 4.1 Numerical Results; 4.2 Identifiability and Sensitivity Analysis; 5 Discrete-Time Model; 5.1 Numerical Simulations; 5.2 Sensitivity Analysis; 6 Discussion; 7 Conclusions and Future Directions; 8 Data Availability; Appendix; Model Analysis of Continuous-Time Model; Model Analysis of Discrete-Time Model; References; A Mathematical Model for Tumor-Immune Dynamics in Multiple Myeloma; 1 Introduction; 2 Mathematical Model 2.1 Evidence for Model Pathways2.2 A Reduced Model for the Diseased State; 3 Equilibria and Stability; 3.1 Analysis of Trivial Equilibrium Points: TC*=0; 3.2 Number of Positive Equilibrium Points: TC*>0; 3.3 Stability of Positive Equilibrium Points: TC*>0; 3.4 Numerical Illustration and Interpretation of the Results; 4 Conclusion and Future Work; Appendix; Existence and Uniqueness of Solutions; Scaled Model; Stability of Trivial Equilibria for M<Mc; Algebraic Simplification for Positive Equilibria; References; Fluid Dynamics of Nematocyst Prey Capture; 1 Background and Motivation; 2 Methods
• Publisher Details: Cham? : Springer
• Publication Date: 2018
• Extent: 1 online resource (207 pages)
• Subjects: 571.7; Mathematics; Biological systems -- Mathematics; Systems biology -- Mathematics; SCIENCE / Life Sciences / Anatomy & Physiology; Mathematics -- Applied; Maths for scientists; Electronic books
• Languages: English
• ISBNs: 3319980831; 9783319980836
• Related ISBNs: 3319980823; 9783319980829
• Notes: Note: Includes bibliographical references and index.; Note: Online resource; title from PDF title page (EBSCO, Nov. 29, 2018).
• Access Rights: Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
• Access Usage: Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.