Theoretical physics for biological systems

Theoretical physics for biological systems /

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Bibliographic Details
Main Author: Lecca, Paola, 1973- (Author)
Corporate Author: ProQuest (Firm)
Format: Electronic eBook
Language:English
Published: Boca Raton, FL : RC Press, Taylor & Francis Group, [2019]
Subjects:
Biophysics.
Biological systems.
Online Access:Connect to this title online (unlimited simultaneous users allowed; 325 uses per year)
Table of Contents:
  • Machine generated contents note: 1. Quantum Mechanics in Biology
  • 1.1. General Definitions
  • 1.2. Time-independent Schrodinger Equation
  • 1.3. Time-dependent Schrodinger Equation
  • 1.4. Transition Probability Per Unit of Time
  • 1.5. Quantum Coherence and Entanglement
  • 1.6. Quantum Interference
  • 1.7. Quantum Effects in Biology
  • 2. Statistical Physics in Biology
  • 2.1. Why Statistical Physics in Biology?
  • 2.2. Markov Processes
  • 2.3. Chemical Master Equation
  • 2.4. Chemical Master Equation and Curse of Dimensionality
  • 2.5. Discrete Approach to Chemical Kinetics
  • 2.5.1. Effective Reactions are Inelastic Collisions
  • 2.5.2. Factors Affecting Reaction Rate
  • 2.6. Stochastic Simulation Algorithm
  • 2.7. Example of Real Enzymatic Reactions Simulated with Gillespie Algorithm
  • 3. Graph Theory and Physics Meet Network Biology
  • 3.1. Physics at the Birth of Network Biology
  • 3.2. Mutual Information-Based Network Inference
  • 3.3. Thermodynamics Applications in Biological Network Analysis
  • 3.3.1. Vibrational Centrality
  • 3.3.2. Network Entropy: A graph theory based definition
  • 3.4. Electronic Physics Applications in Network Analysis
  • 3.5. Assessment of Network Inference Methods and the Issue of Generation of Gold-Standard Data
  • 3.6. Network Biology is Transformed by Physics
  • 4. Applied Descriptors for Complexity and Centrality to Network Biology
  • 4.1. Network Theory
  • 4.2. Measures for Network Complexity and Centrality
  • 4.2.1. Network Entropy: A statistical mechanics and quantum physics definition
  • 4.3. Comparative Network Analysis
  • 4.3.1. Maximum Likelihood Estimation and Model Selection
  • 4.3.2. Reducibility of Multiplex Networks
  • 4.4. Applications
  • 4.4.1. Node Ranking in Biological Networks
  • 4.4.2. Entropy-Based Estimation of Differentiation Potency
  • 4.4.3. Entropy-Based Hallmark of Cancer
  • 5. Perspectives
  • 5.1. Systems Theory and Quantum Physics
  • 5.2. Various Recapitulation Exercises.

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