Volume Effects in Chemotaxis

Size: px
Start display at page:

Download "Volume Effects in Chemotaxis"

Transcription

1 Volume Effects in Chemotaxis Thomas Hillen University of Alberta supported by NSERC with Kevin Painter (Edinburgh), Volume Effects in Chemotaxis p.1/48

2 Eschirichia coli Berg - Lab (Harvard) Volume Effects in Chemotaxis p.2/48

3 Azotobacter vinelandii Page - Lab (Edmonton) Volume Effects in Chemotaxis p.3/48

4 Dictyostelium discoideum Firtel - Lab (US San Diego): Volume Effects in Chemotaxis p.4/48

5 Relevance in ecology oriented movement Volume Effects in Chemotaxis p.5/48

6 Relevance in ecology oriented movement chemotaxis models as prototype Volume Effects in Chemotaxis p.5/48

7 Relevance in ecology oriented movement chemotaxis models as prototype pattern formation and spatial distributions. Volume Effects in Chemotaxis p.5/48

8 Relevance in ecology oriented movement chemotaxis models as prototype pattern formation and spatial distributions. extinction and coexistence. Volume Effects in Chemotaxis p.5/48

9 Relevance in ecology oriented movement chemotaxis models as prototype pattern formation and spatial distributions. extinction and coexistence. prey-taxis (with Lee, Lewis). Volume Effects in Chemotaxis p.5/48

10 Outline (1) The Classical Chemotaxis Equations Volume Effects in Chemotaxis p.6/48

11 Outline (1) The Classical Chemotaxis Equations (2) Derivation from a Master Equation Volume Effects in Chemotaxis p.6/48

12 Outline (1) The Classical Chemotaxis Equations (2) Derivation from a Master Equation (3) The Volume Filling Approach Volume Effects in Chemotaxis p.6/48

13 Outline (1) The Classical Chemotaxis Equations (2) Derivation from a Master Equation (3) The Volume Filling Approach (4) The Quorum Sensing Approach Volume Effects in Chemotaxis p.6/48

14 Outline (1) The Classical Chemotaxis Equations (2) Derivation from a Master Equation (3) The Volume Filling Approach (4) The Quorum Sensing Approach (5) The Finite Sampling Radius Approach Volume Effects in Chemotaxis p.6/48

15 Outline (1) The Classical Chemotaxis Equations (2) Derivation from a Master Equation (3) The Volume Filling Approach (4) The Quorum Sensing Approach (5) The Finite Sampling Radius Approach (6) Other Approaches (pressure, multi-phase flows) Volume Effects in Chemotaxis p.6/48

16 Outline (1) The Classical Chemotaxis Equations (2) Derivation from a Master Equation (3) The Volume Filling Approach (4) The Quorum Sensing Approach (5) The Finite Sampling Radius Approach (6) Other Approaches (pressure, multi-phase flows) (7) Conclusions Volume Effects in Chemotaxis p.6/48

17 Outline (1) The Classical Chemotaxis Equations (2) Derivation from a Master Equation (3) The Volume Filling Approach (4) The Quorum Sensing Approach (5) The Finite Sampling Radius Approach (6) Other Approaches (pressure, multi-phase flows) (7) Conclusions (8) Future Research Volume Effects in Chemotaxis p.6/48

18 (1) The Classical Chemotaxis Model : particle density : concentration of chemical signal : diffusion coefficient, chemotactic sensitivity production and consumption of signal. Volume Effects in Chemotaxis p.7/48

19 References Patlak 1953 Volume Effects in Chemotaxis p.8/48

20 References Patlak 1953 Keller + Segel 1970 Volume Effects in Chemotaxis p.8/48

21 References Patlak 1953 Keller + Segel 1970 Volume Effects in Chemotaxis p.8/48

22 References Patlak 1953 Keller + Segel 1970 Othmer + Stevens 1997: The ABC of Chemotaxis. Volume Effects in Chemotaxis p.8/48

23 References Patlak 1953 Keller + Segel 1970 Othmer + Stevens 1997: The ABC of Chemotaxis. Volume Effects in Chemotaxis p.8/48

24 References Patlak 1953 Keller + Segel 1970 Othmer + Stevens 1997: The ABC of Chemotaxis. Horstmann 2004: Review. Volume Effects in Chemotaxis p.8/48

25 References Patlak 1953 Keller + Segel 1970 Othmer + Stevens 1997: The ABC of Chemotaxis. Horstmann 2004: Review. Hillen + Potapov 2004: spikes in 1-D. Volume Effects in Chemotaxis p.8/48

26 Review Dirk Horstmann From 1970 until present: The Keller-Segel model in chemotaxis and its consequences. Part I: Jahresbericht der DMV, Vol. 105 (3), , Part II: Jahresbericht der DMV, Vol. 106 (2), 51-69, Volume Effects in Chemotaxis p.9/48

27 (2) Derivation from a Master Equation Random walk description (Othmer-Stevens 1997) _ T T + i i x x i 1 i i+1 Probability to find a particle at x at time Transitional probabilities per unit of time for one jump to the right (+) or left (-).. Volume Effects in Chemotaxis p.10/48

28 (2) Derivation from a Master Equation Random walk description (Othmer-Stevens 1997) _ T T + i i x x i 1 i i+1 Probability to find a particle at x at time Transitional probabilities per unit of time for one jump to the right (+) or left (-). Master equation:. Volume Effects in Chemotaxis p.10/48

29 Example: Diffusion Assume the grid size is and Volume Effects in Chemotaxis p.11/48

30 Example: Diffusion Assume the grid size is and Volume Effects in Chemotaxis p.11/48

31 : Volume Effects in Chemotaxis p.11/48 Example: Diffusion Assume the grid size is and we find for Hence with

32 Now with Chemotaxis : Concentration of a chemical signal. sensitivity function, Volume Effects in Chemotaxis p.12/48

33 Now with Chemotaxis : Concentration of a chemical signal. sensitivity function, Volume Effects in Chemotaxis p.12/48

34 Continuous Limit : Limit, : chemotactic sensitivity. Volume Effects in Chemotaxis p.13/48

35 Continuous Limit Limit :, : chemotactic sensitivity. Volume Effects in Chemotaxis p.13/48

36 Results on Spikes and Finite Time Blow Up x time Volume Effects in Chemotaxis p.14/48

37 Theorem 1 ( ) (Childress, Percus, Jäger, Luckhaus, Nagai, Senba, Yoshida, Herrero, Velazquez, Levine, Sleeman, Gajewski, Zacharias, Biler, Post, Horstmann, Suzuki, Yagi, Potapov, Hillen, Renclawowicz, etc ) Volume Effects in Chemotaxis p.15/48

38 Theorem 1 ( ) (Childress, Percus, Jäger, Luckhaus, Nagai, Senba, Yoshida, Herrero, Velazquez, Levine, Sleeman, Gajewski, Zacharias, Biler, Post, Horstmann, Suzuki, Yagi, Potapov, Hillen, Renclawowicz, etc ) Volume Effects in Chemotaxis p.15/48

39 Theorem 1 ( ) (Childress, Percus, Jäger, Luckhaus, Nagai, Senba, Yoshida, Herrero, Velazquez, Levine, Sleeman, Gajewski, Zacharias, Biler, Post, Horstmann, Suzuki, Yagi, Potapov, Hillen, Renclawowicz, etc ) 1-D: Spike formation, no blow-up. Volume Effects in Chemotaxis p.15/48

40 Theorem 1 ( ) (Childress, Percus, Jäger, Luckhaus, Nagai, Senba, Yoshida, Herrero, Velazquez, Levine, Sleeman, Gajewski, Zacharias, Biler, Post, Horstmann, Suzuki, Yagi, Potapov, Hillen, Renclawowicz, etc ) 1-D: Spike formation, no blow-up. 2-D: There exists a threshold such that blow-up boundary blow-up no blow-up Volume Effects in Chemotaxis p.15/48

41 Theorem 1 ( ) (Childress, Percus, Jäger, Luckhaus, Nagai, Senba, Yoshida, Herrero, Velazquez, Levine, Sleeman, Gajewski, Zacharias, Biler, Post, Horstmann, Suzuki, Yagi, Potapov, Hillen, Renclawowicz, etc ) 1-D: Spike formation, no blow-up. 2-D: There exists a threshold such that blow-up boundary blow-up no blow-up n-d: There is a threshold as well (Renclawowicz, Hillen 2005). Volume Effects in Chemotaxis p.15/48

42 So What? Volume Effects in Chemotaxis p.16/48

43 So What? Question 1: What does finite time blow-up tell us about the biology? Volume Effects in Chemotaxis p.16/48

44 So What? Question 1: What does finite time blow-up tell us about the biology? Question 2: What does finite time blow-up tell us about the modeling? Volume Effects in Chemotaxis p.16/48

45 Volume Effects Volume Filling (H, Painter) Volume Effects in Chemotaxis p.17/48

46 Volume Effects Volume Filling (H, Painter) Quorum Sensing (H, Painter) Volume Effects in Chemotaxis p.17/48

47 Volume Effects Volume Filling (H, Painter) Quorum Sensing (H, Painter) Finite Sampling Radius (H, Painter, Schmeiser) Volume Effects in Chemotaxis p.17/48

48 Volume Effects Volume Filling (H, Painter) Quorum Sensing (H, Painter) Finite Sampling Radius (H, Painter, Schmeiser) Pressure (Preziosi et al.) Volume Effects in Chemotaxis p.17/48

49 Volume Effects Volume Filling (H, Painter) Quorum Sensing (H, Painter) Finite Sampling Radius (H, Painter, Schmeiser) Pressure (Preziosi et al.) Multi-phase flow (Owen et al.) Volume Effects in Chemotaxis p.17/48

50 (3) The Volume Filling Approach (w. K. Painter) Increasing chemoattractant concentration A B C Volume Effects in Chemotaxis p.18/48

51 (3) The Volume Filling Approach (w. K. Painter) Increasing chemoattractant concentration A B C Introduce probability to find space at a local cell density Volume Effects in Chemotaxis p.18/48

52 (3) The Volume Filling Approach (w. K. Painter) Increasing chemoattractant concentration A B C Introduce Assumption probability to find space at a local cell density max and for all max Volume Effects in Chemotaxis p.18/48

53 (3) The Volume Filling Approach (w. K. Painter) Increasing chemoattractant concentration A B C Introduce Assumption probability to find space at a local cell density max and for all max Standard example: max Volume Effects in Chemotaxis p.18/48

54 The Volume Filling Model Volume Effects in Chemotaxis p.19/48

55 The Volume Filling Model Substitute into the above master equation and let : Volume Effects in Chemotaxis p.19/48

56 Complete Picture [1]-[7] [1] Hillen + Painter 2000: First mention of the volume filling model; proof of global existence for special cases; numerical pattern formation. Volume Effects in Chemotaxis p.20/48

57 Complete Picture [1]-[7] [1] Hillen + Painter 2000: First mention of the volume filling model; proof of global existence for special cases; numerical pattern formation. If the domain is large enough we obtain non trivial steady states. u(x) τ (x) Volume Effects in Chemotaxis p.20/48

58 Pattern Formation in 1-D. cell density log 10 t space 30 Volume Effects in Chemotaxis p.21/48

59 Pattern Formation in 2-D (top), (middle), (bottom) Volume Effects in Chemotaxis p.22/48

60 Complete Picture [1]-[7] [1] Hillen + Painter 2000: Volume Effects in Chemotaxis p.23/48

61 Complete Picture [1]-[7] [1] Hillen + Painter 2000: [2] Painter + Hillen 2002: Derivation from a random walk description, pattern formation, coarsening. Volume Effects in Chemotaxis p.23/48

62 Complete Picture [1]-[7] [1] Hillen + Painter 2000: [2] Painter + Hillen 2002: Derivation from a random walk description, pattern formation, coarsening. [3] D. Wrzosek 2003: Existence of a compact global attractor. Volume Effects in Chemotaxis p.23/48

63 Complete Picture [1]-[7] [1] Hillen + Painter 2000: [2] Painter + Hillen 2002: Derivation from a random walk description, pattern formation, coarsening. [3] D. Wrzosek 2003: Existence of a compact global attractor. [4] D. Wrzosek 2004: Lyapunov function. -limit sets are steady states. Volume Effects in Chemotaxis p.23/48

64 Complete Picture [1]-[7] [5] Potapov + Hillen 2004: Bifurcation diagram, metastability, numerical estimates of leading eigenvalues, scaling analysis and pattern interaction. Volume Effects in Chemotaxis p.24/48

65 Complete Picture [1]-[7] [5] Potapov + Hillen 2004: Bifurcation diagram, metastability, numerical estimates of leading eigenvalues, scaling analysis and pattern interaction. Bifurcation Diagram Volume Effects in Chemotaxis p.24/48

66 Complete Picture [1]-[7] [6] Dolak + Schmeiser 2004: Asymptotic analysis of pattern interaction. Volume Effects in Chemotaxis p.25/48

67 Complete Picture [1]-[7] [6] Dolak + Schmeiser 2004: Asymptotic analysis of pattern interaction. [7] Dolak + Hillen 2003: Application to Dictyostelium discoideum and to Salmonella typhimurium. Volume Effects in Chemotaxis p.25/48

68 Application to Dictyostelium discoideum Volume Effects in Chemotaxis p.26/48

69 Application to Salmonella typhimurium Volume Effects in Chemotaxis p.27/48

70 (4) The Quorum Sensing Approach Increasing chemoattractant concentration (b) quorum based approach : concentration of quorum sensing molecule. Volume Effects in Chemotaxis p.28/48

71 (4) The Quorum Sensing Approach Increasing chemoattractant concentration (b) quorum based approach : concentration of quorum sensing molecule. Case 1: Interfering substances Volume Effects in Chemotaxis p.28/48

72 (4) The Quorum Sensing Approach Increasing chemoattractant concentration (b) quorum based approach : concentration of quorum sensing molecule. Case 1: Interfering substances Case 2: Non-interfering substances Volume Effects in Chemotaxis p.28/48

73 Derivation: quorum sensing Case 1: Interfering substances Volume Effects in Chemotaxis p.29/48

74 Volume Effects in Chemotaxis p.29/48 Derivation: quorum sensing Case 1: Interfering substances

75 Derivation: quorum sensing Special case of, equilibrates fast monotonic function Volume Effects in Chemotaxis p.30/48

76 Derivation: quorum sensing Special case of, equilibrates fast Then monotonic function a volume filling model follows. Volume Effects in Chemotaxis p.30/48

77 Derivation: quorum sensing Case 2: Non-interfering substances Volume Effects in Chemotaxis p.31/48

78 Volume Effects in Chemotaxis p.31/48 Derivation: quorum sensing Case 2: Non-interfering substances

79 Quorum sensing, case 1, in 2-D Ring-shaped patterns: Chi = 2.0 Chi = 5.0 Chi= Volume Effects in Chemotaxis p.32/48

80 Quorum sensing in 1-D Quorum sensing model (case 2, attraction-repulsion) Hopf bifurcations possible. Volume Effects in Chemotaxis p.33/48

81 Quorum sensing in 1-D Quorum sensing model (case 2, attraction-repulsion) Hopf bifurcations possible. time space Volume Effects in Chemotaxis p.33/48

82 Analysis of the non-interfering model (w. J. Renclawowicz) Volume Effects in Chemotaxis p.34/48

83 Analysis of the non-interfering model (w. J. Renclawowicz) Some rescaling: Volume Effects in Chemotaxis p.34/48

84 Concentration difference, Introduce Volume Effects in Chemotaxis p.35/48

85 Concentration difference, Introduce Special case:, : Volume Effects in Chemotaxis p.35/48

86 Concentration difference, Introduce Special case:, : Volume Effects in Chemotaxis p.35/48

87 Concentration difference, Introduce Special case:, : repulsive case:, attractive case:. Volume Effects in Chemotaxis p.35/48

88 Results on the Quorum Sensing Model (w. J. Renclawowicz) For attractive and repulsive case: Local existence. Volume Effects in Chemotaxis p.36/48

89 Results on the Quorum Sensing Model (w. J. Renclawowicz) For attractive and repulsive case: Local existence.. Volume Effects in Chemotaxis p.36/48

90 Results on the Quorum Sensing Model (w. J. Renclawowicz) For attractive and repulsive case: Local existence.. In -D, global existence. Norm-estimates of Hillen + Potapov Volume Effects in Chemotaxis p.36/48

91 Results on the Quorum Sensing Model (w. J. Renclawowicz) For attractive and repulsive case: Local existence.. In -D, global existence. Norm-estimates of Hillen + Potapov D, Assume : and solutions exist globally in time. New proof based on estimates. are small. Then Volume Effects in Chemotaxis p.36/48

92 More Results For the attractive case: -D: Lyapunov function. Modify Gajewsky + Zacharias 1998 and Biler 1998 for. Consequence: Global existence below a threshold. Volume Effects in Chemotaxis p.37/48

93 More Results For the attractive case: -D: Lyapunov function. Modify Gajewsky + Zacharias 1998 and Biler 1998 for. Consequence: Global existence below a threshold -D: Existence of blow-up solutions. apply Herrero-Velazquez Volume Effects in Chemotaxis p.37/48

94 Open Questions for Quorum Sensing Global existence for the repulsive case in -D. Volume Effects in Chemotaxis p.38/48

95 Open Questions for Quorum Sensing Global existence for the repulsive case in Hopf bifurcation and periodic solutions. -D. Volume Effects in Chemotaxis p.38/48

96 (5) Finite Sampling Radius (with Painter and Schmeiser) Volume Effects in Chemotaxis p.39/48

97 (5) Finite Sampling Radius (with Painter and Schmeiser) Othmer, H (2002): Nonlocal gradient: Sampling radius. Volume Effects in Chemotaxis p.39/48

98 (5) Finite Sampling Radius (with Painter and Schmeiser) Othmer, H (2002): Nonlocal gradient: Sampling radius. (i) If const. then. (ii) For each we have Volume Effects in Chemotaxis p.39/48

99 Volume Effects in Chemotaxis p.40/48 Modified Model

100 Volume Effects in Chemotaxis p.40/48 Modified Model Theorem : global existence.,

101 Simulations Volume Effects in Chemotaxis p.41/48

102 (6) Other Approaches Volume Effects in Chemotaxis p.42/48

103 Preziosi et al mass and momentum conservation: : pressure : velocity. Volume Effects in Chemotaxis p.43/48

104 Preziosi et al mass and momentum conservation: : pressure : velocity. Aggregation and mesh formation, application to vasculature. Volume Effects in Chemotaxis p.43/48

105 Relation to Volume Filling Given, then Volume Effects in Chemotaxis p.44/48

106 Relation to Volume Filling Given, then Given, then Volume Effects in Chemotaxis p.44/48

107 Owen, Byrne 2005 Two phase flow: cells, water. Volume Effects in Chemotaxis p.45/48

108 Owen, Byrne 2005 Two phase flow: cells Chemotaxis equation:, water. Volume Effects in Chemotaxis p.45/48

109 Owen, Byrne 2005 Two phase flow: cells, water. Chemotaxis equation: : chemotactic stress : interphase drag strength. Volume Effects in Chemotaxis p.45/48

110 (8) Conclusions on Blow-up Blow-up describes the onset of aggregation and the underlying instability very well. Volume Effects in Chemotaxis p.46/48

111 (8) Conclusions on Blow-up Blow-up describes the onset of aggregation and the underlying instability very well. Blow-up models are singular limit cases of more realistic models. Volume Effects in Chemotaxis p.46/48

112 (8) Conclusions on Blow-up Blow-up describes the onset of aggregation and the underlying instability very well. Blow-up models are singular limit cases of more realistic models. More realistic models include volume effects. Volume Effects in Chemotaxis p.46/48

113 Conclusions on Volume Effects Volume Effects in Chemotaxis p.47/48

114 Conclusions on Volume Effects Volume Filling Relatively easy to include into a model. Volume Effects in Chemotaxis p.47/48

115 Conclusions on Volume Effects Volume Filling Relatively easy to include into a model. Leads to global existence and pattern formation. Attractors and bifurcations are understood. Volume Effects in Chemotaxis p.47/48

116 Conclusions on Volume Effects Volume Filling Relatively easy to include into a model. Leads to global existence and pattern formation. Attractors and bifurcations are understood. Quorum Sensing Can show all phenomena, blow-up, spikes, or global patterns. Volume Effects in Chemotaxis p.47/48

117 Conclusions on Volume Effects Volume Filling Relatively easy to include into a model. Leads to global existence and pattern formation. Attractors and bifurcations are understood. Quorum Sensing Can show all phenomena, blow-up, spikes, or global patterns. Open questions: Global existence for the repulsive case, and Hopf bifurcation. Volume Effects in Chemotaxis p.47/48

118 Conclusions on Volume Effects Volume Filling Relatively easy to include into a model. Leads to global existence and pattern formation. Attractors and bifurcations are understood. Quorum Sensing Can show all phenomena, blow-up, spikes, or global patterns. Open questions: Global existence for the repulsive case, and Hopf bifurcation. Finite Sampling Radius The finite sampling radius immediately regularizes the problem. Volume Effects in Chemotaxis p.47/48

119 Conclusions on Volume Effects Volume Filling Relatively easy to include into a model. Leads to global existence and pattern formation. Attractors and bifurcations are understood. Quorum Sensing Can show all phenomena, blow-up, spikes, or global patterns. Open questions: Global existence for the repulsive case, and Hopf bifurcation. Finite Sampling Radius The finite sampling radius immediately regularizes the problem. Open question: -D? Volume Effects in Chemotaxis p.47/48

120 Conclusions on Volume Effects Volume Filling Relatively easy to include into a model. Leads to global existence and pattern formation. Attractors and bifurcations are understood. Quorum Sensing Can show all phenomena, blow-up, spikes, or global patterns. Open questions: Global existence for the repulsive case, and Hopf bifurcation. Finite Sampling Radius The finite sampling radius immediately regularizes the problem. Open question: -D? Open question: Does the non local gradient have additional regularity properties? Volume Effects in Chemotaxis p.47/48

121 (8) Future Research Chemotaxis of D. discoideum, S. typhimurium, E. coli, etc. on the population level are well understood and well modeled. Volume Effects in Chemotaxis p.48/48

122 (8) Future Research Chemotaxis of D. discoideum, S. typhimurium, E. coli, etc. on the population level are well understood and well modeled. Current research focusses on the individual movement behavior. Volume Effects in Chemotaxis p.48/48

123 (8) Future Research Chemotaxis of D. discoideum, S. typhimurium, E. coli, etc. on the population level are well understood and well modeled. Current research focusses on the individual movement behavior. Other applications, like endothelial cells. Volume Effects in Chemotaxis p.48/48

124 (8) Future Research Chemotaxis of D. discoideum, S. typhimurium, E. coli, etc. on the population level are well understood and well modeled. Current research focusses on the individual movement behavior. Other applications, like endothelial cells. angiogenesis, tumor growth, cancer therapies. Volume Effects in Chemotaxis p.48/48

125 (8) Future Research Chemotaxis of D. discoideum, S. typhimurium, E. coli, etc. on the population level are well understood and well modeled. Current research focusses on the individual movement behavior. Other applications, like endothelial cells. angiogenesis, tumor growth, cancer therapies. wound healing. Volume Effects in Chemotaxis p.48/48

126 (8) Future Research Chemotaxis of D. discoideum, S. typhimurium, E. coli, etc. on the population level are well understood and well modeled. Current research focusses on the individual movement behavior. Other applications, like endothelial cells. angiogenesis, tumor growth, cancer therapies. wound healing. development, pigmentation patterns. Volume Effects in Chemotaxis p.48/48

127 (8) Future Research Chemotaxis of D. discoideum, S. typhimurium, E. coli, etc. on the population level are well understood and well modeled. Current research focusses on the individual movement behavior. Other applications, like endothelial cells. angiogenesis, tumor growth, cancer therapies. wound healing. development, pigmentation patterns. in ecology. Volume Effects in Chemotaxis p.48/48

Mathematical Methods for Cancer Invasion

Mathematical Methods for Cancer Invasion Mathematical Methods for Cancer Invasion Takashi Suzuki Osaka University Cell Movement Physiological morphogenesis wound healing cellular immunity Pathological inflammation arteriosclerosis cancer invasion,

More information

Title: Understanding the role of linker histone in DNA packaging with mathematical modelling

Title: Understanding the role of linker histone in DNA packaging with mathematical modelling Gustavo Carrero Araujo, Athabasca University Title: Understanding the role of linker histone in DNA packaging with mathematical modelling Abstract: When we think of the approximate average length of DNA

More information

Mathematical biology From individual cell behavior to biological growth and form

Mathematical biology From individual cell behavior to biological growth and form Mathematical biology From individual cell behavior to biological growth and form Lecture 8: Multiscale models Roeland Merks (1,2) (1) Centrum Wiskunde & Informatica, Amsterdam (2) Mathematical Institute,

More information

Coarse grained simulations of Lipid Bilayer Membranes

Coarse grained simulations of Lipid Bilayer Membranes Coarse grained simulations of Lipid Bilayer Membranes P. B. Sunil Kumar Department of Physics IIT Madras, Chennai 600036 sunil@iitm.ac.in Atomistic MD: time scales ~ 10 ns length scales ~100 nm 2 To study

More information

A METAPOPULATION MODEL OF GRANULOMA FORMATION IN THE LUNG DURING INFECTION WITH MYCOBACTERIUM TUBERCULOSIS. Suman Ganguli.

A METAPOPULATION MODEL OF GRANULOMA FORMATION IN THE LUNG DURING INFECTION WITH MYCOBACTERIUM TUBERCULOSIS. Suman Ganguli. MATHEMATICAL BIOSCIENCES http://www.mbejournal.org/ AND ENGINEERING Volume, Number 3, August 5 pp. 535 56 A METAPOPULATION MODEL OF GRANULOMA FORMATION IN THE LUNG DURING INFECTION WITH MYCOBACTERIUM TUBERCULOSIS

More information

Angiogenesis and vascular remodelling in normal and cancerous tissues

Angiogenesis and vascular remodelling in normal and cancerous tissues J. Math. Biol. (29) 58:689 721 DOI 1.17/s285-8-213-z Mathematical Biology Angiogenesis and vascular remodelling in and cancerous tissues Markus R. Owen Tomás Alarcón Philip K. Maini Helen M. Byrne Received:

More information

Cell-based modeling of angiogenic blood vessel sprouting

Cell-based modeling of angiogenic blood vessel sprouting Cell-based modeling of angiogenic blood vessel sprouting Roeland Merks Biomodeling & Biosystems Analysis Centrum Wiskunde & Informatica - Life Sciences Netherlands Institute for Systems Biology Netherlands

More information

BMBF Forsys Partner Project: A Systems Biology Approach towards Predictive Cancer Therapy

BMBF Forsys Partner Project: A Systems Biology Approach towards Predictive Cancer Therapy ling and ling and BMBF Forsys Partner Project: A Systems Biology Approach towards Predictive Cancer Therapy H. Perfahl, A. Lapin, M. Reuss Germany holger.perfahl@ibvt.uni-stuttgart.de 1 ling and Cooperation

More information

Contents 1 Computational Haemodynamics An Introduction 2 The Human Cardiovascular System

Contents 1 Computational Haemodynamics An Introduction 2 The Human Cardiovascular System Contents 1 Computational Haemodynamics An Introduction... 1 1.1 What is Computational Haemodynamics (CHD)... 1 1.2 Advantages of CHD... 3 1.3 Applications in the Cardiovascular System... 4 1.3.1 CHD as

More information

Analyzing Immunotherapy and Chemotherapy of Tumors through Mathematical Modeling Summer Student-Faculty Research Project

Analyzing Immunotherapy and Chemotherapy of Tumors through Mathematical Modeling Summer Student-Faculty Research Project Analyzing Immunotherapy and Chemotherapy of Tumors through Mathematical Modeling Summer Student-Faculty Research Project by Lisette de Pillis, Weiqing Gu, William Chang, Lindsay Crowl, Eric Malm, Katherine

More information

Culturing embryonic tissues in the computer

Culturing embryonic tissues in the computer Culturing embryonic tissues in the computer Blood vessel development Roeland Merks Biomodeling & Biosystems Analysis CWI, Life Sciences and Netherlands Institute for Systems Biology Biological development

More information

Numerical Simulation of Blood Flow through Asymmetric and Symmetric Occlusion in Carotid Artery

Numerical Simulation of Blood Flow through Asymmetric and Symmetric Occlusion in Carotid Artery Proceedings of the 3 rd International Conference on Fluid Flow, Heat and Mass Transfer (FFHMT 16) Ottawa, Canada May 2 3, 2016 Paper No. 170 Numerical Simulation of Blood Flow through Asymmetric and Symmetric

More information

Understanding Sleep-Wake Dynamics with Two Process Model and BDB Model

Understanding Sleep-Wake Dynamics with Two Process Model and BDB Model Understanding Sleep-Wake Dynamics with Two Process Model and BDB Model Diya Sashidhar Advisor: Victoria Booth July 20, 2016 Abstract In this paper, we study the 24 hour sleep-wake cycle as a nonlinear

More information

Simulation of Chemotractant Gradients in Microfluidic Channels to Study Cell Migration Mechanism in silico

Simulation of Chemotractant Gradients in Microfluidic Channels to Study Cell Migration Mechanism in silico Simulation of Chemotractant Gradients in Microfluidic Channels to Study Cell Migration Mechanism in silico P. Wallin 1*, E. Bernson 1, and J. Gold 1 1 Chalmers University of Technology, Applied Physics,

More information

Influence of nonequilibrium lipid transport, membrane compartmentalization, and membrane proteins on the lateral organization of the plasma membrane

Influence of nonequilibrium lipid transport, membrane compartmentalization, and membrane proteins on the lateral organization of the plasma membrane PHYSICAL REVIEW E 81, 1198 1 Influence of nonequilibrium lipid transport, membrane compartmentalization, and membrane proteins on the lateral organization of the plasma membrane Jun Fan and Maria Sammalkorpi

More information

Modeling Imatinib-Treated Chronic Myeloid Leukemia

Modeling Imatinib-Treated Chronic Myeloid Leukemia Modeling Imatinib-Treated Chronic Myeloid Leukemia Cara Peters cpeters3@math.umd.edu Advisor: Dr. Doron Levy dlevy@math.umd.edu Department of Mathematics Center for Scientific Computing and Mathematical

More information

Structured models for dengue epidemiology

Structured models for dengue epidemiology Structured models for dengue epidemiology submitted by Hannah Woodall for the degree of Doctor of Philosophy of the University of Bath Department of Mathematical Sciences September 24 COPYRIGHT Attention

More information

Multiscale Models of Solid Tumor Growth and Angiogenesis: The effect of the microenvironment

Multiscale Models of Solid Tumor Growth and Angiogenesis: The effect of the microenvironment Multiscale Models of Solid Tumor Growth and Angiogenesis: The effect of the microenvironment John Lowengrub Dept Math and Biomed Eng., UCI P. Macklin, Ph.D. 2007 (expected); Vittorio Cristini (UCI/UT Health

More information

Simulating the Tumor Growth with Cellular Automata Models

Simulating the Tumor Growth with Cellular Automata Models Simulating the Tumor Growth with Cellular Automata Models S. Zouhri Université Hassan II- Mohammédia, Faculté des Sciences Ben M'sik Département de Mathématiques, B.7955, Sidi Othmane, Casablanca, Maroc

More information

Computing with Spikes in Recurrent Neural Networks

Computing with Spikes in Recurrent Neural Networks Computing with Spikes in Recurrent Neural Networks Dezhe Jin Department of Physics The Pennsylvania State University Presented at ICS Seminar Course, Penn State Jan 9, 2006 Outline Introduction Neurons,

More information

Multiscale Models of Solid Tumor Growth and Angiogenesis: The effect of the microenvironment

Multiscale Models of Solid Tumor Growth and Angiogenesis: The effect of the microenvironment Multiscale Models of Solid Tumor Growth and Angiogenesis: The effect of the microenvironment John Lowengrub Dept Math and Biomed Eng., UCI P. Macklin, Ph.D. 2007 (expected); Vittorio Cristini (UCI/UT Health

More information

Delay Differential Model for Tumor-Immune Dynamics with HIV Infection of CD4 + T Cells

Delay Differential Model for Tumor-Immune Dynamics with HIV Infection of CD4 + T Cells Delay Differential Model for Tumor-Immune Dynamics with HIV Infection of CD4 + T Cells Fathalla A. Rihan Duaa H. Abdel-Rahman ICM 2012, 11-14 March, Al Ain Abstract In this paper, we introduce a mathematical

More information

Impact of Clustering on Epidemics in Random Networks

Impact of Clustering on Epidemics in Random Networks Impact of Clustering on Epidemics in Random Networks Joint work with Marc Lelarge TREC 20 December 2011 Coupechoux - Lelarge (TREC) Epidemics in Random Networks 20 December 2011 1 / 22 Outline 1 Introduction

More information

Non-Newtonian pulsatile blood flow in a modeled artery with a stenosis and an aneurysm

Non-Newtonian pulsatile blood flow in a modeled artery with a stenosis and an aneurysm Non-Newtonian pulsatile blood flow in a modeled artery with a stenosis and an aneurysm I. Husain, C. Langdon and J. Schwark Department of Mathematics Luther College University of Regina Regina, Saskatchewan

More information

Numerical simulations of fluid mechanical interactions between two abdominal aortic branches

Numerical simulations of fluid mechanical interactions between two abdominal aortic branches Korea-Australia Rheology Journal Vol. 16, No. 2, June 2004 pp. 75-83 Numerical simulations of fluid mechanical interactions between two abdominal aortic branches Taedong Kim, Taewon Seo* 1,2 and Abdul.I.

More information

Study 1 Effect of Alcohol Dose on Mouse Movement

Study 1 Effect of Alcohol Dose on Mouse Movement Name: Pd: Date: Geophysics Study 1 Effect of Alcohol Dose on Mouse Movement This study investigates the effect of different levels of alcohol consumption on the activity (movement) of mice. The experiment

More information

The Cancer and Ligand Show! A spectacle in five acts.

The Cancer and Ligand Show! A spectacle in five acts. The Cancer and Ligand Show! A spectacle in five acts. Outline 1) 2) 3) 4) 5) Mystery fun times Model Overview Equations COMSOL Tutorial Parameter Sweeps Hint: This Mary Poppins chimney sweep is surprisingly

More information

Dynamique des populations et résistance aux traitements : modèles mathématiques

Dynamique des populations et résistance aux traitements : modèles mathématiques Dynamique des populations et résistance aux traitements : modèles mathématiques Alexander Lorz 1 R. Chisholm, J. Clairambault, A. Escargueil, M.E. Hochberg, T. Lorenzi, P. Markowich, B. Perthame, E. Trélat

More information

Mathematical modeling of cancer cell invasion of tissue: biological insight from mathematical analysis and computational simulation

Mathematical modeling of cancer cell invasion of tissue: biological insight from mathematical analysis and computational simulation J. Math. Biol. () 6:4 7 DOI.7/s85--69- Mathematical Biology Mathematical modeling of cancer cell invasion of tissue: biological insight from mathematical analysis and computational simulation Vivi Andasari

More information

Multiscale Modeling and Mathematical Problems Related to Tumor Evolution and Medical Therapy*

Multiscale Modeling and Mathematical Problems Related to Tumor Evolution and Medical Therapy* Journal of Theoretical Medicine, June 2003 Vol. 5 (2), pp. 111 136 Review Article Multiscale Modeling and Mathematical Problems Related to Tumor Evolution and Medical Therapy* NICOLA BELLOMO, ELENA DE

More information

A Patient-Specific Anisotropic Diffusion Model for Brain Tumor Spread

A Patient-Specific Anisotropic Diffusion Model for Brain Tumor Spread Noname manuscript No. (will be inserted by the editor) A Patient-Specific Anisotropic Diffusion Model for Brain Tumor Spread Amanda Swan Thomas Hillen John C. Bowman Albert D. Murtha Received: date / Accepted:

More information

Project Report: Swarm Behavior and Control

Project Report: Swarm Behavior and Control 1 Project Report: Swarm Behavior and Control Xiaofeng Han Kevin Ridgley Scott Johnson Megan Keenan Swarm Team One University of Delaware {xiaofeng,kridgley,scottj,mkeenan}@udel.edu I. INTRODUCTION Aggregations

More information

EGFR model presentation E L Z A R A K I M A L O V A A L E X S M I T H

EGFR model presentation E L Z A R A K I M A L O V A A L E X S M I T H EGFR model presentation E L Z A R A K I M A L O V A A L E X S M I T H What are we going to talk about? Phenomena of the Sos-EGF dose response curve (length of run) Talking about dimers when rules are for

More information

EMERGING PATTERNS IN CROWD STREAMS AND THE AID OF ABM FOR EGRESS MANAGEMENT

EMERGING PATTERNS IN CROWD STREAMS AND THE AID OF ABM FOR EGRESS MANAGEMENT F.A. Ponziani, et al., Int. J. of Design & Nature and Ecodynamics. Vol. 11 No. 4 (2016) 543 552 EMERGING PATTERNS IN CROWD STREAMS AND THE AID OF ABM FOR EGRESS MANAGEMENT F.A. PONZIANI 1,2, A. TINABURRI

More information

Computational Fluid Dynamics Analysis of Blalock-Taussig Shunt

Computational Fluid Dynamics Analysis of Blalock-Taussig Shunt Washington University in St. Louis Washington University Open Scholarship Mechanical Engineering and Materials Science Independent Study Mechanical Engineering & Materials Science 12-23-2017 Computational

More information

Mathematics of Infectious Diseases

Mathematics of Infectious Diseases Mathematics of Infectious Diseases Zhisheng Shuai Department of Mathematics University of Central Florida Orlando, Florida, USA shuai@ucf.edu Zhisheng Shuai (U Central Florida) Mathematics of Infectious

More information

Large Graph Mining: Power Tools and a Practitioner s guide

Large Graph Mining: Power Tools and a Practitioner s guide Large Graph Mining: Power Tools and a Practitioner s guide Task 6: Virus/Influence Propagation Faloutsos, Miller,Tsourakakis CMU KDD'09 Faloutsos, Miller, Tsourakakis P6-1 Outline Introduction Motivation

More information

Intro. Comp. NeuroSci. Ch. 9 October 4, The threshold and channel memory

Intro. Comp. NeuroSci. Ch. 9 October 4, The threshold and channel memory 9.7.4 The threshold and channel memory The action potential has a threshold. In figure the area around threshold is expanded (rectangle). A current injection that does not reach the threshold does not

More information

Mathematics 4MB3/6MB3 Mathematical Biology

Mathematics 4MB3/6MB3 Mathematical Biology Mathematics and Statistics dω = ω M M Mathematics 4MB3/6MB3 Mathematical Biology Instructor: Guillaume Blanchet Lecture 22 Synchrony - Part 6 March 4 th 2015 Application of simple coherence criteria 10

More information

A Dynamic model of Pulmonary Vein Electrophysiology. Harry Green 2 nd year Ph.D. student University of Exeter

A Dynamic model of Pulmonary Vein Electrophysiology. Harry Green 2 nd year Ph.D. student University of Exeter A Dynamic model of Pulmonary Vein Electrophysiology Harry Green 2 nd year Ph.D. student University of Exeter Background to the Project Cardiac disease is the leading cause of death in most developed countries

More information

Modeling Tumor-Induced Angiogenesis in the Cornea. An Honors Thesis. Presented by Heather Harrington. Group members Marc Maier Lé Santha Naidoo

Modeling Tumor-Induced Angiogenesis in the Cornea. An Honors Thesis. Presented by Heather Harrington. Group members Marc Maier Lé Santha Naidoo Modeling Tumor-Induced Angiogenesis in the Cornea An Honors Thesis Presented by Heather Harrington Group members Marc Maier Lé Santha Naidoo Submitted May 2005 Guidance Committee Approval: Professor Nathaniel

More information

Simulations of the blood flow in the arterio-venous fistula for haemodialysis

Simulations of the blood flow in the arterio-venous fistula for haemodialysis Acta of Bioengineering and Biomechanics Vol. 16, No. 1, 2014 Original paper DOI: 10.5277/abb140109 Simulations of the blood flow in the arterio-venous fistula for haemodialysis DANIEL JODKO*, DAMIAN OBIDOWSKI,

More information

SPATIAL DISTRIBUTION OF PROTEIN CONCENTRATION CAN CONTROL CELLULAR PATHWAY FLUXES

SPATIAL DISTRIBUTION OF PROTEIN CONCENTRATION CAN CONTROL CELLULAR PATHWAY FLUXES SPATIAL DISTRIBUTION OF PROTEIN CONCENTRATION CAN CONTROL CELLULAR PATHWAY FLUXES BENG 221 October 21, 2011 INTRODUCTION One of the goals of systems biology is to create models for intracellular pathway

More information

Multiscale modelling and nonlinear simulation of vascular tumour growth

Multiscale modelling and nonlinear simulation of vascular tumour growth J. Math. Biol. (2009) 58:765 798 DOI 10.1007/s00285-008-0216-9 Mathematical Biology Multiscale modelling and nonlinear simulation of vascular tumour growth Paul Macklin Steven McDougall Alexander R. A.

More information

Mathematical Model Approach To HIV/AIDS Transmission From Mother To Child

Mathematical Model Approach To HIV/AIDS Transmission From Mother To Child Mathematical Model Approach To HIV/AIDS Transmission From Mother To Child Basavarajaiah.D. M. B. Narasimhamurthy, K. Maheshappa. B. Leelavathy ABSTRACT:- AIDS is a devastating disease, more than 2.50 million

More information

Mathematics of Infectious Diseases Modélisation mathématique des maladies infectieuses (Org: Abba Gumel (Manitoba))

Mathematics of Infectious Diseases Modélisation mathématique des maladies infectieuses (Org: Abba Gumel (Manitoba)) Mathematics of Infectious Diseases Modélisation mathématique des maladies infectieuses (Org: Abba Gumel (Manitoba)) CHRISTOPHER BOWMAN, Inst. for Biodiagnostics FRED BRAUER, University of British Columbia

More information

Modeling the muscular response to motor neuron spike-trains. Laura Miller and Katie Newhall SAMSI Transition Workshop May 4, 2016

Modeling the muscular response to motor neuron spike-trains. Laura Miller and Katie Newhall SAMSI Transition Workshop May 4, 2016 Modeling the muscular response to motor neuron spike-trains Laura Miller and Katie Newhall SAMSI Transition Workshop May 4, 2016 Outline 1. Motivation for an integrative neural and mechanical view of animal

More information

Imperfect, Unlimited-Capacity, Parallel Search Yields Large Set-Size Effects. John Palmer and Jennifer McLean. University of Washington.

Imperfect, Unlimited-Capacity, Parallel Search Yields Large Set-Size Effects. John Palmer and Jennifer McLean. University of Washington. Imperfect, Unlimited-Capacity, Parallel Search Yields Large Set-Size Effects John Palmer and Jennifer McLean University of Washington Abstract Many analyses of visual search assume error-free component

More information

Feature Integration Theory

Feature Integration Theory Feature Integration Theory Project guide: Amitabha Mukerjee Course: SE367 Presented by Harmanjit Singh Feature Integration Theory Treisman, Sykes, & Gelade, 1977 Features are registered early, automatically,

More information

The Rescorla Wagner Learning Model (and one of its descendants) Computational Models of Neural Systems Lecture 5.1

The Rescorla Wagner Learning Model (and one of its descendants) Computational Models of Neural Systems Lecture 5.1 The Rescorla Wagner Learning Model (and one of its descendants) Lecture 5.1 David S. Touretzky Based on notes by Lisa M. Saksida November, 2015 Outline Classical and instrumental conditioning The Rescorla

More information

Mathematical Assessment of anti-hpv Vaccines

Mathematical Assessment of anti-hpv Vaccines Mathematical Assessment of anti-hpv Vaccines Abba B. Gumel, Department of Mathematics, University of Manitoba, Winnipeg, Manitoba, Canada., Fields Institute, November 6, 2013. Burden of Some Infectious

More information

Herding Behavior: The emergence of large-scale phenomena from local interactions

Herding Behavior: The emergence of large-scale phenomena from local interactions Herding Behavior: The emergence of large-scale phenomena from local interactions Dennis Chao Simon Levin March 5, 2007 Keywords: herding; grouping; collective behavior; individual-based models; wildebeest

More information

We parameterized a coarse-grained fullerene consistent with the MARTINI coarse-grained force field

We parameterized a coarse-grained fullerene consistent with the MARTINI coarse-grained force field Parameterization of the fullerene coarse-grained model We parameterized a coarse-grained fullerene consistent with the MARTINI coarse-grained force field for lipids 1 and proteins 2. In the MARTINI force

More information

Heroin Epidemic Models

Heroin Epidemic Models Heroin Epidemic Models icholas A. Battista Intro to Math Biology Project School of Mathematical Sciences, Rochester Institute of Technology, 85 Lomb Memorial Drive, Rochester, Y 14623-5603, USA May 21,

More information

Mathematical biology From individual cell behavior to biological growth and form

Mathematical biology From individual cell behavior to biological growth and form Mathematical biology From individual cell behavior to biological growth and form Lecture 6: Branching morphogenesis Roeland Merks (1,2) (1) Centrum Wiskunde & Informatica, Amsterdam (2) Mathematical Institute,

More information

Simulations of pulsatile blood flow in tapered S-shaped inplane and out-of-plane coronary arteries

Simulations of pulsatile blood flow in tapered S-shaped inplane and out-of-plane coronary arteries Simulations of pulsatile blood flow in tapered S-shaped inplane and out-of-plane coronary arteries Author Johnston, Barbara, Johnston, Peter Published 2009 Conference Title 18th IMACS World Congress MODSIM09

More information

A Cell-based Model of Endothelial Cell Migration, Proliferation and Maturation During Corneal Angiogenesis

A Cell-based Model of Endothelial Cell Migration, Proliferation and Maturation During Corneal Angiogenesis Bulletin of Mathematical Biology (2010) 72: 830 868 DOI 10.1007/s11538-009-9471-1 ORIGINAL ARTICLE A Cell-based Model of Endothelial Cell Migration, Proliferation and Maturation During Corneal Angiogenesis

More information

MMSE Interference in Gaussian Channels 1

MMSE Interference in Gaussian Channels 1 MMSE Interference in Gaussian Channels Shlomo Shamai Department of Electrical Engineering Technion - Israel Institute of Technology 202 Information Theory and Applications Workshop 5-0 February, San Diego

More information

A Mathematical Model for Capillary Network Formation in the Absence of Endothelial Cell Proliferation

A Mathematical Model for Capillary Network Formation in the Absence of Endothelial Cell Proliferation Pergamon Appl. Math. Lett. Vol. 11, No. 3, pp. 109-114, 1998 Copyright(~)1998 Elsevier Science Ltd Printed in Great Britain. All rights reserved 0893-9659/98 $19.00 + 0.00 PII: S0893-9659(98)00041-X A

More information

Influence of anti-viral drug therapy on the evolution of HIV-1 pathogens

Influence of anti-viral drug therapy on the evolution of HIV-1 pathogens Influence of anti-viral drug therapy on the evolution of HIV-1 pathogens and Libin Rong Department of Mathematics Purdue University Outline HIV-1 life cycle and Inhibitors Age-structured models with combination

More information

PHYSIOLOGICAL PULSATILE WAVEFORM THROUGH AXISYMMETRIC STENOSED ARTERIES: NUMERICAL SIMULATION

PHYSIOLOGICAL PULSATILE WAVEFORM THROUGH AXISYMMETRIC STENOSED ARTERIES: NUMERICAL SIMULATION PHYSIOLOGICAL PULSATILE WAVEFORM THROUGH AXISYMMETRIC STENOSED ARTERIES: NUMERICAL SIMULATION Jayme Pinto Ortiz University of São Paulo - Avenida Prof. Luciano Gualberto, travessa3 nº 380 - CEP - 05508-900

More information

CHEMOTACTIC SIGNALS AND RESPONSES ARE COORDINATED BY AN OSCILLATORY CIRCUIT IN DICTYOSTELIUM

CHEMOTACTIC SIGNALS AND RESPONSES ARE COORDINATED BY AN OSCILLATORY CIRCUIT IN DICTYOSTELIUM CHEMOTACTIC SIGNALS AND RESPONSES ARE COORDINATED BY AN OSCILLATORY CIRCUIT IN DICTYOSTELIUM Dr. William Loomis, UCSD (KITP Bio Networks Chemotaxis Workshop 3/12/03) 1 Dictyostelium is a social amoeba

More information

Date: Thursday, 1 May :00AM

Date: Thursday, 1 May :00AM Cancer can give you Maths! Transcript Date: Thursday, 1 May 2008-12:00AM CANCER CAN GIVE YOU MATHS! Professor Philip Maini I would like to start off by thanking Gresham College for this invitation. I am

More information

Flip-Flop Induced Relaxation Of Bending Energy: Implications For Membrane Remodeling

Flip-Flop Induced Relaxation Of Bending Energy: Implications For Membrane Remodeling Biophysical Journal, Volume 97 Supporting Material Flip-Flop Induced Relaxation Of Bending Energy: Implications For Membrane Remodeling Raphael Jeremy Bruckner, Sheref S. Mansy, Alonso Ricardo, L. Mahadevan,

More information

modeling, analyses, skills

modeling, analyses, skills modeling, analyses, skills 1 , 2 assumptions 3 4 5 definition of ZPD 6 Needs, attractions, incentives and motives of activity are basic the analyses of play should be started with the analyses of those

More information

Crowd Behavior Modelling in Emergency Situations

Crowd Behavior Modelling in Emergency Situations Mini Project Report Crowd Behavior Modelling in Emergency Situations Supervisor : Prof. Prem Kalra Ankur Jain Gagan Bansal Mansi Matela December 5, 2005 1 Contents 1 Abstract 3 2 Introduction 3 2.1 Related

More information

MBios 478: Systems Biology and Bayesian Networks, 27 [Dr. Wyrick] Slide #1. Lecture 27: Systems Biology and Bayesian Networks

MBios 478: Systems Biology and Bayesian Networks, 27 [Dr. Wyrick] Slide #1. Lecture 27: Systems Biology and Bayesian Networks MBios 478: Systems Biology and Bayesian Networks, 27 [Dr. Wyrick] Slide #1 Lecture 27: Systems Biology and Bayesian Networks Systems Biology and Regulatory Networks o Definitions o Network motifs o Examples

More information

Mathematical Model of the Chronic Lymphocytic Leukemia Microenvironment

Mathematical Model of the Chronic Lymphocytic Leukemia Microenvironment Mathematical Model of the Chronic Lymphocytic Leukemia Microenvironment Ben Fogelson Lisette depillis, Advisor Rachel Levy, Reader May, 2009 Department of Mathematics Copyright c 2009 Ben Fogelson. The

More information

arxiv: v3 [q-bio.to] 9 Apr 2009

arxiv: v3 [q-bio.to] 9 Apr 2009 MATHEMATICAL BIOSCIENCES AND ENGINEERING Volume xx, Number 0xx, xx 20xx http://www.mbejournal.org/ pp. 1 xx A SPATIAL MODEL OF TUMOR-HOST INTERACTION: APPLICATION OF CHEMOTHERAPY arxiv:0810.1024v3 [q-bio.to]

More information

FFR Fundamentals and Measurements

FFR Fundamentals and Measurements FFR Fundamentals and Measurements Ghassan S. Kassab Thomas Linnemeier Chair Professor Biomedical Engineering, Indiana University Purdue University Indianapolis Principle of FFR Q S ( P P ) / R P max d

More information

Modeling Three-dimensional Invasive Solid Tumor Growth in Heterogeneous Microenvironment under Chemotherapy

Modeling Three-dimensional Invasive Solid Tumor Growth in Heterogeneous Microenvironment under Chemotherapy Modeling Three-dimensional Invasive Solid Tumor Growth in Heterogeneous Microenvironment under Chemotherapy Hang Xie 1, Yang Jiao 2, Qihui Fan 3, Miaomiao Hai 1, Jiaen Yang 1, Zhijian Hu 1, Yue Yang 4,

More information

Diabetes Protocol Using Nitric Oxide Therapy

Diabetes Protocol Using Nitric Oxide Therapy ATTENTION: Life enhancing information specifically tailored to those with diabetes. Diabetes Protocol Using Nitric Oxide Therapy This Diabetes Protocol is divided into 4 sections. The 1st section contains

More information

Blood flow induced wall stress in the left ventricle of the heart

Blood flow induced wall stress in the left ventricle of the heart Blood flow induced wall stress in the left ventricle of the heart A. K. Macpherson 1, S. Neti 1, J. A. Mannisi 2 & P. A. Macpherson 3 1 Institute for Biomedical Engineering and Mathematical Biology, Lehigh

More information

This module illustrates SEM via a contrast with multiple regression. The module on Mediation describes a study of post-fire vegetation recovery in

This module illustrates SEM via a contrast with multiple regression. The module on Mediation describes a study of post-fire vegetation recovery in This module illustrates SEM via a contrast with multiple regression. The module on Mediation describes a study of post-fire vegetation recovery in southern California woodlands. Here I borrow that study

More information

A Cell-Based Model Exhibiting Branching and Anastomosis during Tumor-Induced Angiogenesis

A Cell-Based Model Exhibiting Branching and Anastomosis during Tumor-Induced Angiogenesis Biophysical Journal Volume 92 May 2007 3105 3121 3105 A Cell-Based Model Exhibiting Branching and Anastomosis during Tumor-Induced Angiogenesis Amy L. Bauer,* Trachette L. Jackson,* and Yi Jiang y *Department

More information

Mathematical modelling of spatio-temporal glioma evolution

Mathematical modelling of spatio-temporal glioma evolution Papadogiorgaki et al. Theoretical Biology and Medical Modelling 213, 1:47 RESEARCH Open Access Mathematical modelling of spatio-temporal glioma evolution Maria Papadogiorgaki 1*, Panagiotis Koliou 2, Xenofon

More information

Pattern formation at cellular membranes by phosphorylation and dephosphorylation of proteins

Pattern formation at cellular membranes by phosphorylation and dephosphorylation of proteins Pattern formation at cellular membranes by phosphorylation and dephosphorylation of proteins Sergio Alonso Department of Mathematical modeling and data analysis Physikalisck-Technische Bundesanstalt &

More information

Information and Communication Technologies EPIWORK. Developing the Framework for an Epidemic Forecast Infrastructure.

Information and Communication Technologies EPIWORK. Developing the Framework for an Epidemic Forecast Infrastructure. Information and Communication Technologies EPIWORK Developing the Framework for an Epidemic Forecast Infrastructure http://www.epiwork.eu Project no. 231807 D1.1 Analysis of Epidemic Dynamics on Clustered

More information

Determination of the Diffusion Coefficient for Sucrose in Aqueous Solutions

Determination of the Diffusion Coefficient for Sucrose in Aqueous Solutions CHEM 332L Physical Chemistry Laboratory II Revision 1.1 Determination of the Diffusion Coefficient for Sucrose in Aqueous Solutions In this laboratory exercise we will measure the diffusion coefficient

More information

A virtual pharmacokinetic model of human eye

A virtual pharmacokinetic model of human eye A virtual pharmacokinetic model of human eye Sreevani Kotha 1, Lasse Murtomäki 1,2 1 University of Helsinki, Centre for Drug Research 2 Aalto University, School of Chemical Technology, Department of Chemistry

More information

Simulation of blood flow through endovascular prosthesis in patients with Abdominal Aortic Aneurysm

Simulation of blood flow through endovascular prosthesis in patients with Abdominal Aortic Aneurysm Simulation of blood flow through endovascular prosthesis in patients with Abdominal Aortic Aneurysm Andrzej Polańczyk, MSc Ireneusz Zbiciński, PhD, DSc Abstract The aim of this study was to estimate whether

More information

arxiv: v1 [q-bio.to] 2 Jan 2015

arxiv: v1 [q-bio.to] 2 Jan 2015 A Mathematical Model for Lymphangiogenesis in Normal and Diabetic Wounds Arianna Bianchi a, Kevin J. Painter a, Jonathan A. Sherratt a arxiv:1501.00421v1 [q-bio.to] 2 Jan 2015 a Department of Mathematics

More information

A mathematical insight in the epithelial-mesenchymal-like transition in cancer cells and its effect in the invasion of the extracellular matrix

A mathematical insight in the epithelial-mesenchymal-like transition in cancer cells and its effect in the invasion of the extracellular matrix Bull Braz Math Soc, New Series 47(1), 397-412 2016, Sociedade Brasileira de Matemática ISSN: 1678-7544 (Print) / 1678-7714 (Online) A mathematical insight in the epithelial-mesenchymal-like transition

More information

3.1 The Lacker/Peskin Model of Mammalian Ovulation

3.1 The Lacker/Peskin Model of Mammalian Ovulation Mammalian Ovulation 3.1 The Lacker/Peskin Model of Mammalian Ovulation Reference: Regulation of Ovulation Number in Mammals A large reserve pool of follicles is formed before birth in many female mammals.

More information

Cerebrospinal fluid flow in the upper cervical canal in patients with the Chiari I malformation

Cerebrospinal fluid flow in the upper cervical canal in patients with the Chiari I malformation Cerebrospinal fluid flow in the upper cervical canal in patients with the Chiari I malformation Kent-Andre Mardal K. H. Støverud, S. Linge, G. Rutkowska, I. Drøsdal, H.P. Langtangen, V. Haughton Outline

More information

Mathematical Model of Cartilage Regeneration via Hydrogel Honors Thesis, Wittenberg University Department of Mathematics

Mathematical Model of Cartilage Regeneration via Hydrogel Honors Thesis, Wittenberg University Department of Mathematics Daniel Marous Mathematical Model of Cartilage Regeneration via Hydrogel Honors Thesis, Wittenberg University Department of Mathematics Abstract Because of the large number of individuals with cartilage

More information

Cover Page. The handle holds various files of this Leiden University dissertation.

Cover Page. The handle   holds various files of this Leiden University dissertation. Cover Page The handle http://hdl.handle.net/1887/28967 holds various files of this Leiden University dissertation. Author: Palm, Margaretha Maria (Margriet) Title: High-throughput simulation studies of

More information

Guided Cell Migration: A Dynamical Systems Perspective. Wolfgang Losert. Department of Physics, University of Maryland

Guided Cell Migration: A Dynamical Systems Perspective. Wolfgang Losert. Department of Physics, University of Maryland Guided Cell Migration: A Dynamical Systems Perspective Wolfgang Losert Department of Physics, University of Maryland Guided Cell Migration is Essential for Living Systems Phil Keller, Janelia Farm Development

More information

Feedback Mechanism for Microtubule Length Regulation by Stathmin Gradients

Feedback Mechanism for Microtubule Length Regulation by Stathmin Gradients Feedback Mechanism for Microtubule Length Regulation by Stathmin Gradients Maria Zeitz, Jan Kierfeld Physics Department, TU Dortmund University, 44221 Dortmund, Germany December 2, 214 Abstract We formulate

More information

μ i = chemical potential of species i C i = concentration of species I

μ i = chemical potential of species i C i = concentration of species I BIOE 459/559: Cell Engineering Membrane Permeability eferences: Water Movement Through ipid Bilayers, Pores and Plasma Membranes. Theory and eality, Alan Finkelstein, 1987 Membrane Permeability, 100 Years

More information

modelling the role of Essential Fatty Acids in aquatic food webs

modelling the role of Essential Fatty Acids in aquatic food webs modelling the role of Essential Fatty Acids in aquatic food webs Gurbir Perhar, George B. Arhonditsis University of Toronto Ecology & Evolutionary Biology g.perhar@utoronto.ca AGENDA: Introduction Objectives

More information

A mathematical model for the capillary endothelial cell-extracellular matrix interactions in wound-healing angiogenesis

A mathematical model for the capillary endothelial cell-extracellular matrix interactions in wound-healing angiogenesis IMA Journal of Mathematics Applied in Medicine & Biology (1997) 14, 261-281 A mathematical model for the capillary endothelial cell-extracellular matrix interactions in wound-healing angiogenesis LUKE

More information

Cécile Baron 1, Carine Guivier-Curien 2, Vu-Hieu Nguyen 3, Salah Naili 3. Monastery Banz, June 29 th, 2017

Cécile Baron 1, Carine Guivier-Curien 2, Vu-Hieu Nguyen 3, Salah Naili 3. Monastery Banz, June 29 th, 2017 Bone repair and ultrasound stimulation : an insight into the interaction of LIPUS with the lacuno-canalicular network of cortical bone through a multiscale computational study. Cécile Baron 1, Carine Guivier-Curien

More information

An application of topological relations of fuzzy regions with holes

An application of topological relations of fuzzy regions with holes Chapter 5 An application of topological relations of fuzzy regions with holes 5.1 Introduction In the last two chapters, we have provided theoretical frameworks for fuzzy regions with holes in terms of

More information

Formation of multistranded β-lactoglobulin amyloid fibrils and their stimuli responsive magnetic behaviour in the lyotropic liquid crystals

Formation of multistranded β-lactoglobulin amyloid fibrils and their stimuli responsive magnetic behaviour in the lyotropic liquid crystals Formation of multistranded β-lactoglobulin amyloid fibrils and their stimuli responsive magnetic behaviour in the lyotropic liquid crystals Sreenath Bolisetty Prof. Raffaele Mezzenga Food & Soft Materials

More information

Application of Fuzzy Cellular Neural Network and its Stability to Color Edge Detection

Application of Fuzzy Cellular Neural Network and its Stability to Color Edge Detection Proceedings of the International Conference on Applied Mathematics Theoretical Computer Science - 2013 1 Application of Fuzzy Cellular Neural Network its Stability to Color Edge Detection M. Kalpana P.

More information

Introduction to the High Jump The high jump is a track and field event that requires athletes to jump over a heightened horizontal bar by jumping off

Introduction to the High Jump The high jump is a track and field event that requires athletes to jump over a heightened horizontal bar by jumping off 1 Introduction to the High Jump The high jump is a track and field event that requires athletes to jump over a heightened horizontal bar by jumping off of only one foot. The high jump can be broken into

More information

Interaction of ultrasound with cortical bone as a two-level porous medium: a multiscale computational study.

Interaction of ultrasound with cortical bone as a two-level porous medium: a multiscale computational study. Interaction of ultrasound with cortical bone as a two-level porous medium: a multiscale computational study. Cécile Baron 1, Carine Guivier-Curien 2, Vu-Hieu Nguyen 3, Salah Naili 3 1 Aix-Marseille Université,

More information

Programs for facies modeling with DMPE

Programs for facies modeling with DMPE Programs for facies modeling with DMPE Yupeng Li and Clayton V. Deutsch The programs needed for direct multivariate probability estimation (DMPE) are introduced in detail. The first program (TPcalc) is

More information

Irina V. Ionova, Vsevolod A. Livshits, and Derek Marsh

Irina V. Ionova, Vsevolod A. Livshits, and Derek Marsh Phase Diagram of Ternary Cholesterol/Palmitoylsphingomyelin/Palmitoyloleoyl- Phosphatidylcholine Mixtures: Spin-abel EPR Study of ipid-raft Formation Irina V. Ionova, Vsevolod A. ivshits, and Derek Marsh

More information