Automated Reasoning for Systems Biology and Medicine

• Corporate Author: SpringerLink (Online service)
• Other Authors: Liò, Pietro (Editor, http://id.loc.gov/vocabulary/relators/edt), Zuliani, Paolo (Editor, http://id.loc.gov/vocabulary/relators/edt)
• Format: Electronic eBook
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2019.
• Edition: 1st ed. 2019.
• Series: Computational Biology, 30
• Subjects: Bioinformatics.; Systems biology.; Artificial intelligence.; Health informatics.; Pattern recognition.; Computational Biology/Bioinformatics.; Systems Biology.; Artificial Intelligence.; Health Informatics.; Pattern Recognition.

This book presents outstanding contributions in an exciting, new and multidisciplinary research area: the application of formal, automated reasoning techniques to analyse complex models in systems biology and systems medicine. Automated reasoning is a field of computer science devoted to the develop...

Table of Contents:

• Part I: Model Checking
• Chapter 1. Model Checking Approach to the Analysis of Biological Systems
• Chapter2. Automated Reasoning for the Synthesis and Analysis of Biological Programs
• Chapter 3. Statistical Model Checking based Analysis Techniques of Biological Networks
• Chapter 4. Models, Devices, Properties and Verification for the Artificial Pancreas
• Chapter 5. Using State Space Exploration to Determine How Gene Regulatory Networks Constrain Mutation Order in Cancer Evolution
• Part II: Formal Methods and Logic
• Chapter 6. Set-based Analysis for Biological Modelling
• Chapter 7. Logic and Linear Programs to Understand Cancer Response
• Chapter 8. Logic-Based Formalization of System Requirements for Integrated Clinical Environments
• Chapter 9. Balancing prescriptions with Constraint Solvers
• Chapter 10. Metastable Regimes and Tipping Points of Biochemical Networks with Potential Applications in Precision Medicine
• Part III: Stochastic Modelling and Analysis.-Chapter 11. Stochastic Spatial Modelling of the Remyelination Process in Multiple Sclerosis Lesions
• Chapter 12. Approximation Techniques for Stochastic Analysis of Biological Systems
• Chapter 13. A Graphical Approach for the Hybrid Modelling of Intracellular Calcium Dynamics Based on Coloured Hybrid Petri Nets
• Chapter 14. Methods for Personalised Delivery Rate Computation for IV Administered Anesthetic Propofol
• Part IV: Machine Learning and Artificial Intelligence
• Chapter 15. Towards the Integration of Metabolic Network Modelling and Machine Learning for the Routine Analysis of High-Throughput Patient Data
• Chapter 16. Opportunities and Challenges in Applying Artificial Intelligence to Bioengineering
• Chapter 17. Deep Learning with Convolutional Neural Networks for Histopathology Image Analysis.