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Realistic modeling and rendering of plant ecosystems
 SCIENTIFIC VISUALIZATION LABORATORY, DEPARTMENT OF COMPUTER SCIENCE, TEXAS A&M UNIVERSITY, COLLEGE STATION, TX 778433112
, 1998
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Abstract machines of systems biology
 Transactions on Computational Systems Biology
, 2005
"... Abstract. Living cells are extremely wellorganized autonomous systems, consisting of discrete interacting components. Key to understanding and modeling their behavior is modeling their system organization. Four distinct chemical toolkits (classes of macromolecules) have been characterized, each com ..."
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Cited by 47 (2 self)
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Abstract. Living cells are extremely wellorganized autonomous systems, consisting of discrete interacting components. Key to understanding and modeling their behavior is modeling their system organization. Four distinct chemical toolkits (classes of macromolecules) have been characterized, each combinatorial in nature. Each toolkit consists of a small number of simple components that are assembled (polymerized) into complex structures that interact in rich ways. Each toolkit abstracts away from chemistry; it embodies an abstract machine with its own instruction set and its own peculiar interaction model. These interaction models are highly effective, but are not ones commonly used in computing: proteins stick together, genes have fixed output, membranes carry activity on their surfaces. Biologists have invented a number of notations attempting to describe these abstract machines and the processes they implement. Moving up from molecular biology, systems biology aims to understand how these interaction models work, separately and together. 1
A Modelling Method and User Interface for Creating Plants
 IN PROCEEDINGS OF GRAPHICS INTERFACE 97
, 1997
"... We present a modelling method and graphical user interface for the creation of natural branching structures such as plants. Structural and geometric information is encapsulated in objects that are combined to form a description of the model. The description is represented graphically as an icon tree ..."
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Cited by 41 (5 self)
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We present a modelling method and graphical user interface for the creation of natural branching structures such as plants. Structural and geometric information is encapsulated in objects that are combined to form a description of the model. The description is represented graphically as an icon tree and can be edited interactively. Global and partial constraint techniques are integrated on the basis of tropisms and allow the modelling of specific shapes. We show examples to illustrate the design process and evaluate the user interface.
Modeling and visualization of leaf venation patterns
"... We introduce a class of biologically−motivated algorithms for generating leaf venation patterns. These algorithms simulate the interplay between three processes: (1) development of veins towards hormone (auxin) sources embedded in the leaf blade; (2) modification of the hormone source distribution ..."
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Cited by 40 (7 self)
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We introduce a class of biologically−motivated algorithms for generating leaf venation patterns. These algorithms simulate the interplay between three processes: (1) development of veins towards hormone (auxin) sources embedded in the leaf blade; (2) modification of the hormone source distribution by the proximity of veins; and (3) modification of both the vein pattern and source distribution by leaf growth. These processes are formulated in terms of iterative geometric operations on sets of points that represent vein nodes and auxin sources. In addition, a vein connection graph is maintained to determine vein widths. The effective implementation of the algorithms relies on the use of space subdivision (Voronoi diagrams) and time coherence between iteration steps. Depending on the specification details and parameters used, the algorithms can simulate many types of venation patterns, both open (tree−like) and closed (with loops). Applications of the presented algorithms include texture and detailed structure generation for image synthesis purposes, and modeling of morphogenetic processes in support of biological research.
Reactivity, Concurrency, DataFlow and Hierarchical Preemption for Behavioural Animation
 Programming Paradigms in Graphics’95, Eurographics Collection
, 1995
"... Behavioural models offer the ability to simulate autonomous entities like organisms and living beings. Such entities are able to perceive their environment, to communicate with other creatures and to execute some decided actions either on themselves or on their environment. Building such systems r ..."
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Cited by 16 (10 self)
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Behavioural models offer the ability to simulate autonomous entities like organisms and living beings. Such entities are able to perceive their environment, to communicate with other creatures and to execute some decided actions either on themselves or on their environment. Building such systems requires the design of a reactive system treating flows of data to and from its environment, in a complex way needing modularity, concurrency and hierarchy, and involving task control and preemption. Accordingly, in this paper we address the adequateness to the decisional part of the behavioural model of the following programming paradigms: reactivity, concurrency, dataflow and hierarchical preemption. The reactive languages provide users with complete design environments (including graphical tools for designing, simulating, implementing and formally verifying) for such systems. The specification of concurrent behaviours is naturally supported in the synchronous languages, and some of...
The artificial life of plants
 In Artificial Life for Graphics, Animation, and Virtual Reality, v7 of SIGGRAPH
, 1995
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Visualization of Developmental Processes By Extrusion in Space Time
 PROCEEDINGS OF GRAPHICS INTERFACE ’96
, 1996
"... Developmental processes in nature may involve complex changes in the topology, shape, and patterns of growing structures. Processes taking place in one or two dimensions can be visualized as objects in threedimensional space, obtained by extruding the growing structures along a line or curve repres ..."
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Cited by 14 (5 self)
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Developmental processes in nature may involve complex changes in the topology, shape, and patterns of growing structures. Processes taking place in one or two dimensions can be visualized as objects in threedimensional space, obtained by extruding the growing structures along a line or curve representing the progress of time. In this paper, we extend the notion of Lsystems with turtle interpretation to facilitate the construction of such objects. This extension is based on the interpretation of the entire derivation graph generated by an Lsystem, as opposed to the interpretation of individual words. We illustrate the proposed method by applying it to visualize the development of compound leaves, a sea shell with a pigmentation pattern, and a filamentous bacteria. In addition to serving as visualization examples, these models are of interest on their own. The sea shell model uses an Lsystem to express a reactiondiffusion process, thus relating these two models of morphogenesis. The model of bacteria, which is also of the reactiondiffusion type, sheds new light on one of the basic problems of morphogenesis, the formation of equally spaced organs in a developing medium.
Stochastic process semantics for dynamical grammar syntax: an overview. In:
 Ninth International Symposium on Artificial Intelligence and Mathematics,
, 2006
"... Abstract We define a class of probabilistic models in terms of an operator algebra of stochastic processes, and a representation for this class in terms of stochastic parameterized grammars. A syntactic specification of a grammar is formally mapped to semantics given in terms of a ring of operators ..."
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Cited by 13 (8 self)
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Abstract We define a class of probabilistic models in terms of an operator algebra of stochastic processes, and a representation for this class in terms of stochastic parameterized grammars. A syntactic specification of a grammar is formally mapped to semantics given in terms of a ring of operators, so that composition of grammars corresponds to operator addition or multiplication. The operators are generators for the timeevolution of stochastic processes. The dynamical evolution occurs in continuous time but is related to a corresponding discretetime dynamics. An expansion of the exponential of such timeevolution operators can be used to derive a variety of simulation algorithms. Within this modeling framework one can express data clustering models, logic programs, ordinary and stochastic differential equations, branching processes, graph grammars, and stochastic chemical reaction kinetics. The mathematical formulation connects these apparently distant fields to one another and to mathematical methods from quantum field theory and operator algebra. Such broad expressiveness makes the framework particularly suitable for applications in machine learning and multiscale scientific modeling.
Solving differential equations in developmental models of multicellular structures using Lsystems
 Lecture Notes in Computer Science 3037 (Proceedings of the International Conference in Computational Science ICCS 2004, Krakow
, 2004
"... Mathematical modeling of growing multicellular structures creates the problem of solving systems of equations in which not only the values of variables, but the equations themselves, may change over time. We consider this problem in the framework of Lindenmayer systems, a standard formalism for mode ..."
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Cited by 10 (5 self)
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Mathematical modeling of growing multicellular structures creates the problem of solving systems of equations in which not only the values of variables, but the equations themselves, may change over time. We consider this problem in the framework of Lindenmayer systems, a standard formalism for modeling plants, and show how parametric context−sensitive L−systems can be used to numerically solve growing systems of coupled differential equations. We illustrate our technique with a developmental model of the multicellular bacterium Anabaena. Reference P. Federl and P. Prusinkiewicz: Solving differential equations in developmental models of multicellular