An introduction to systems biology :
Alon, Uri
An introduction to systems biology : design principles of biological circuits Uri Alon - 2nd Ed. - Boca Raton, Florida : CRC Press, ©2020. - xviii, 324 pages : illustrations (some color) ; 26 cm. - Mathematical and computational biology Chapman & Hall/CRC mathematical and computational biology series .
Part 1. Network motifs --
Chapter 1 Transcription networks: basic concepts. Introduction; The cognitive problem of the cell ; Elements of transcription networks ; Dynamics and response time of simple regulation ; Further reading ; Exercises ; Bibliography --
Chapter 2 Autoregulation: a network motif. Introduction ; Patterns, randomized networks and network motifs ; Autoregulation is a network motif ; Negative autoregulation speeds the response time of gene circuits ; Negative autoregulation promotes robustness to fluctuations in production rate ; Summary: Evolution as an engineer ; Further reading ; Exercises ; Bibliography --
Chapter 3 The feed forward loop network motif. Introduction ; The feedforward loop is a network motif ; The structure of the feedforward loop gene circuit ; Dynamics of the coherent Type-1 FFL and AND logic ; The C1-FFL is a sign-sensitive delay element ; OR-Gate C1-FFL is a sign-sensitive delay for OFF steps ; The incoherent Type-1 FFL generates pulses of output ; The other six FFL types can also act as filters and pulse generators ; Convergent evolution of FFLs ; Summary ; Further reading ; Exercises ; Bibliography --
Chapter 4 Temporal programs and the global structure of transcription networks. Introduction ; The single-input module (SIM) network motif ; The SIM can generate temporal gene expression programs ; The multi-output feedforward loop ; The multi-output FFL can generate FIFO temporal programs ; Signal integration by BI-Fans and dense-overlapping regulons ; Network motifs and the global structure of sensory transcription networks ; Interlocked feedforward loops in the B. subtilis sporulation network ; Further reading ; Exercises ; Bibliography --
Chapter 5 Positive feedback, bistability and memory. Network motifs in developmental transcription networks ; Network motifs in protein-protein interaction networks ; Network motifs in neuronal networks ; Reflection ; Further reading --
Chapter 6 How to build a biological oscillator. Oscillations require negative feedback and delay ; Noise can induce oscillations in systems that have only damped oscillations on paper ; Delay oscillations ; Many biological oscillators have a coupled positive and negative feedback loop motif ; Robust bistability using two positive feedback loops ; Further reading ; Exercises ; Bibliography -- Part 2. Robustness --
Chapter 7 Kinetic proofreading and conformational proofreading. Introduction ; Kinetic proofreading of the genetic code can reduce error rates ; Recognition of self and non-self by the immune system ; Kinetic proofreading occurs in diverse processes in the cell ; Conformational proofreading provides specificity without consuming energy ; Demand rules for gene regulation can minimize errors ; Further reading ; Exercises ; Bibliography --
Chapter 8 Robust signalling by bifunctional componets. Robust input-output curves ; Simple signaling circuits are not robust ; Bacterial two-component systems can achieve robustness ; Further reading ; Exercises ; Bibliography --
Chapter 9 Robustness in bacterial chemotaxis. Introduction ; Bacterial chemotaxis, or how bacteria think ; The chemotaxis protein circuit ; The Barkai-Leibler model of exact adaptation ; Individuality and robustness in bacterial chemotaxis ; Further reading ; Exercises ; Bibliography --
Chapter 10 Fold-change detection. Universal features of sensory systems ; Fold-change detection in bacterial chemotaxis ; FCD and exact adaptation ; The incoherent feedforward loop can show FCD ; A general condition for FCD ; Identifying FCD circuits from dynamic measurements ; FCD provides robustness to input noise and allows scale-invariant searches ; Further reading ; Exercises ; References --
Chapter 11 Dynamical compensation and mutal resistance in tissues. The insulin-glucose feedback loop ; The minimal model is not robust to changes in insulin sensitivity ; A slow feedback loop on beta-cell numbers provides compensation ; Dynamical compensation allows the circuit to buffer parameter variations ; Type 2 diabetes is linked with instsability due to a U-shaped death curve ; Tissue-level feedback loops are fragile to invasion by mutants that misread the signal ; Biphasic (U-shaped) response curves can protect against mutant takeover ; Summary ; Further reading ; Exercises ; Bibliography --
Chapter 12 Robust spatial patterning in development. The French flag model is not robust ; Increased robustness by self-enhanced morphogen degradation ; Network motifs that provide degradation feedback for robust patterning ; The robustness principle can distinguish between mechanisms of fruit fly patterning ; Further reading ; Exercises ; Bibliography -- Part 3. Optimality --
Chapter 13 Optimal gene circuit design. Introduction ; Optimal expression level of a protein under constant conditions ; To regulate or not to regulate? Optimal regulation in changing environments ; Environmental selection of the feedforward loop network motif ; Inverse ecology ; Further reading ; Exercises ; Bibliography --
Chapter 14 Multi-objective optimality in biology. Introduction ; The fitness landscape picture for a single task ; Multiple tasks are characterized by performance functions ; Pareto optimality in performance space ; Pareto optimality in trait space leads to simple patterns ; Two tasks lead to a line segment, three tasks to a triangle, four to a tetrahedron ; Trade-offs in morphology ; Archetypes can last over geological timescales ; Trade-offs for proteins ; Trade-offs in gene expression ; Division of labor in the individual cells that make up an organ ; Variation within a species lies on the pareto front ; Further reading ; Exercises ; Bibliography --
Chapter 15 Modularity. The astounding speed of evolution ; Modularity is a common feature of engineered and evolved systems ; Modularity is found at all levels of biological organization ; Modularity is not found in simple computer simulatinos of evolution ; Simulated evolution of circuits made of logic gates ; Randomly varying goals cause confusion ; Modularly varying goals lead to spontaneous evolution of modularity ; The more complex the goal, the more MVG speeds up evolution ; Modular goals and biological evolution ; Further reading ; Exercises ; Bibliography --
Written for students and researchers, the second edition of this best-selling textbook continues to offer a clear presentation of design principles that govern the structure and behavior of biological systems. It highlights simple, recurring circuit elements that make up the regulation of cells and tissues. Rigorously classroom-tested, this edition includes new chapters on exciting advances made in the last decade. Features: Includes seven new chapters; The new edition has 189 exercises, the previous edition had 66; offers new examples relevant to human physiology and disease.
9781439837177
Systems biology.
Computational biology.
Biological systems -- Mathematical models.
570.285 / ALO
An introduction to systems biology : design principles of biological circuits Uri Alon - 2nd Ed. - Boca Raton, Florida : CRC Press, ©2020. - xviii, 324 pages : illustrations (some color) ; 26 cm. - Mathematical and computational biology Chapman & Hall/CRC mathematical and computational biology series .
Part 1. Network motifs --
Chapter 1 Transcription networks: basic concepts. Introduction; The cognitive problem of the cell ; Elements of transcription networks ; Dynamics and response time of simple regulation ; Further reading ; Exercises ; Bibliography --
Chapter 2 Autoregulation: a network motif. Introduction ; Patterns, randomized networks and network motifs ; Autoregulation is a network motif ; Negative autoregulation speeds the response time of gene circuits ; Negative autoregulation promotes robustness to fluctuations in production rate ; Summary: Evolution as an engineer ; Further reading ; Exercises ; Bibliography --
Chapter 3 The feed forward loop network motif. Introduction ; The feedforward loop is a network motif ; The structure of the feedforward loop gene circuit ; Dynamics of the coherent Type-1 FFL and AND logic ; The C1-FFL is a sign-sensitive delay element ; OR-Gate C1-FFL is a sign-sensitive delay for OFF steps ; The incoherent Type-1 FFL generates pulses of output ; The other six FFL types can also act as filters and pulse generators ; Convergent evolution of FFLs ; Summary ; Further reading ; Exercises ; Bibliography --
Chapter 4 Temporal programs and the global structure of transcription networks. Introduction ; The single-input module (SIM) network motif ; The SIM can generate temporal gene expression programs ; The multi-output feedforward loop ; The multi-output FFL can generate FIFO temporal programs ; Signal integration by BI-Fans and dense-overlapping regulons ; Network motifs and the global structure of sensory transcription networks ; Interlocked feedforward loops in the B. subtilis sporulation network ; Further reading ; Exercises ; Bibliography --
Chapter 5 Positive feedback, bistability and memory. Network motifs in developmental transcription networks ; Network motifs in protein-protein interaction networks ; Network motifs in neuronal networks ; Reflection ; Further reading --
Chapter 6 How to build a biological oscillator. Oscillations require negative feedback and delay ; Noise can induce oscillations in systems that have only damped oscillations on paper ; Delay oscillations ; Many biological oscillators have a coupled positive and negative feedback loop motif ; Robust bistability using two positive feedback loops ; Further reading ; Exercises ; Bibliography -- Part 2. Robustness --
Chapter 7 Kinetic proofreading and conformational proofreading. Introduction ; Kinetic proofreading of the genetic code can reduce error rates ; Recognition of self and non-self by the immune system ; Kinetic proofreading occurs in diverse processes in the cell ; Conformational proofreading provides specificity without consuming energy ; Demand rules for gene regulation can minimize errors ; Further reading ; Exercises ; Bibliography --
Chapter 8 Robust signalling by bifunctional componets. Robust input-output curves ; Simple signaling circuits are not robust ; Bacterial two-component systems can achieve robustness ; Further reading ; Exercises ; Bibliography --
Chapter 9 Robustness in bacterial chemotaxis. Introduction ; Bacterial chemotaxis, or how bacteria think ; The chemotaxis protein circuit ; The Barkai-Leibler model of exact adaptation ; Individuality and robustness in bacterial chemotaxis ; Further reading ; Exercises ; Bibliography --
Chapter 10 Fold-change detection. Universal features of sensory systems ; Fold-change detection in bacterial chemotaxis ; FCD and exact adaptation ; The incoherent feedforward loop can show FCD ; A general condition for FCD ; Identifying FCD circuits from dynamic measurements ; FCD provides robustness to input noise and allows scale-invariant searches ; Further reading ; Exercises ; References --
Chapter 11 Dynamical compensation and mutal resistance in tissues. The insulin-glucose feedback loop ; The minimal model is not robust to changes in insulin sensitivity ; A slow feedback loop on beta-cell numbers provides compensation ; Dynamical compensation allows the circuit to buffer parameter variations ; Type 2 diabetes is linked with instsability due to a U-shaped death curve ; Tissue-level feedback loops are fragile to invasion by mutants that misread the signal ; Biphasic (U-shaped) response curves can protect against mutant takeover ; Summary ; Further reading ; Exercises ; Bibliography --
Chapter 12 Robust spatial patterning in development. The French flag model is not robust ; Increased robustness by self-enhanced morphogen degradation ; Network motifs that provide degradation feedback for robust patterning ; The robustness principle can distinguish between mechanisms of fruit fly patterning ; Further reading ; Exercises ; Bibliography -- Part 3. Optimality --
Chapter 13 Optimal gene circuit design. Introduction ; Optimal expression level of a protein under constant conditions ; To regulate or not to regulate? Optimal regulation in changing environments ; Environmental selection of the feedforward loop network motif ; Inverse ecology ; Further reading ; Exercises ; Bibliography --
Chapter 14 Multi-objective optimality in biology. Introduction ; The fitness landscape picture for a single task ; Multiple tasks are characterized by performance functions ; Pareto optimality in performance space ; Pareto optimality in trait space leads to simple patterns ; Two tasks lead to a line segment, three tasks to a triangle, four to a tetrahedron ; Trade-offs in morphology ; Archetypes can last over geological timescales ; Trade-offs for proteins ; Trade-offs in gene expression ; Division of labor in the individual cells that make up an organ ; Variation within a species lies on the pareto front ; Further reading ; Exercises ; Bibliography --
Chapter 15 Modularity. The astounding speed of evolution ; Modularity is a common feature of engineered and evolved systems ; Modularity is found at all levels of biological organization ; Modularity is not found in simple computer simulatinos of evolution ; Simulated evolution of circuits made of logic gates ; Randomly varying goals cause confusion ; Modularly varying goals lead to spontaneous evolution of modularity ; The more complex the goal, the more MVG speeds up evolution ; Modular goals and biological evolution ; Further reading ; Exercises ; Bibliography --
Written for students and researchers, the second edition of this best-selling textbook continues to offer a clear presentation of design principles that govern the structure and behavior of biological systems. It highlights simple, recurring circuit elements that make up the regulation of cells and tissues. Rigorously classroom-tested, this edition includes new chapters on exciting advances made in the last decade. Features: Includes seven new chapters; The new edition has 189 exercises, the previous edition had 66; offers new examples relevant to human physiology and disease.
9781439837177
Systems biology.
Computational biology.
Biological systems -- Mathematical models.
570.285 / ALO