- Theoretical physics and theoretical biology
- Structure and function of supramolecular systems in the living cell, and on the development of non-equilibrium statistical mechanical descriptions and efficient computing tools for structural biology
- NAMD: parallel molecular dynamics code designed for high-performance simulation of large biomolecular systems. NAMD scales to hundreds of processors on high-end parallel platforms and tens of processors on commodity clusters using gigabit ethernet.
- Understand how the structures and motions of complex biological systems regulate fundamental functions like DNA transcription, replication, and recombination and the initiation of disease.
- Apply simulation approaches (molecular dynamics, energy minimization, free energy calculations, general molecular modeling) to allow large-scale and long-time studies of biological systems.
- Molecular Modeling and Simulation: An Interdisciplinary Guide
- Computational methods for biomolecular simulation, which seeks to aid in the discovery of the structures and mechanisms that make life possible.
- Scholarly society dedicated to advancing the scientific understanding of living systems through computation
Barry McMullin (Dublin City University)
- Web Accessibility, Artificial Life.
- The DCU ALife Lab
- Exploring the synthesis of basic Autopoietic Agents in Artificial Chemistries
- Understanding the dynamical processes that define biological organization in terms of interactions among molecular components.
- Identifying those properties of a biological system that are necessary consequences of a particular level of organization.
- Towards a theory of biological organization. A programmatic statement.
- AlChemy project -> discontinued
- Develop new computational methods in order to understand complex dynamical phenomena in living systems.
- Artificial Chemistries - A Review (2001)
- Evolutionary computation
- Artificial Chemistries - A Review (2001)
- Computational Biology Center at the T. J. Watson Research Center (IBM)
- Modeling, simulation and visualization of the development of plants.
- Algorithmic Botany(Computer Graphics)
- Visual Models of Morphogenesis
- Computer modeling of life-like complex behavior
- Modelling, control and simulation of life-like, intelligent virtual characters
- Analysis of evolvable virtual-machine information-processing architectures for human-like minds
- Development of the next generation of self evolving computing systems, artificial life forms, Nanotechnology, and virtual reality as an art medium
- Computer vision and graphics, and also in computer-aided design, medical imaging, artificial intelligence, and artificial life.
- Artificial Life, Complexity, Information Theory, Neural Networks, Artificial Intelligence, Cognition, Computer Graphics, Genetic Algorithms, Ecological Simulation, Evolution, Handwriting Recognition
- Polyworld: An Artificial Life System and Computational Ecology (movies)
- Job: Digital god
- Creation: life and how to make it
- Digital evolution.
Moshe Sipper (Ben-Gurion University, Israel)
- Evolutionary Computation
- Bio-Inspired Computing
- Artificial Life
- Dynamics of simple living systems, in particular their evolution.
Charles A. Ofria (The Digital Evolution Laboratory – Michigan State University)
- Interplay between computer science and Darwinian evolution.
Richard Lenski (Michigan State University)
- Experimental evolution
- Bacteria and AVIDA
Maciej Komosinski (Institute of Computing Science - Poznan University of Technology)
- 3D evolution and simulation
- The Selfish Gene
- Emergent Computing. Evolutionary Computing. Bioinformatics & Computationasl Biology.
- Evolutionary and Swarm Design Group: How specific natural design principles - such as mutation & selection, self-organization & self-assembly, and emergent computing through swarm intelligence - can be better understood by developing mathematical and computational models.
- Fantasy, Brain Damage, and My Dreams of Perfectly Simulating Genome Evolution
- Genetic proof that life is extraterrestrial
- The Evolutionary Emergence of Intelligent Behaviours via Computational Natural Selection
- Random Boolean networks
- A Proposal for Using the Ensemble Approach to Understand Genetic Regulatory Networks (Kauffman’s paper in JTB)
- Understanding Genetic Regulatory Networks (Kauffman’s paper in IJA)
- Piecewise-linear models
- Used to deduce the structure and logic of GRN from gene expression and proteomic data.
Other mathematical tools
- Ensemble approach (scale-free networks and “medusa networks”)
- General approach with EC and statistical analysis
- Modeling of gene expression
- Java simulator of genetic regulatory networks
Carter GW (Institute for Systems Biology)
- Inferring network interactions within a cell: review of analytical methods for network interaction inference
Soule C (CNRS & IHES - Institut des hautes etudes scientifiques)
- Mathematical approaches to differentiation and gene regulation (modeling of gene networks) (pdf)
- Modelling the evolution of genetic regulatory networks (evolution of genetic regulatory networks using the Artificial Genome)
- Modelling pathways of cell differentiation in GRN with random Boolean networks (Dealy’s MS thesis at CS – University of New Mexico)
Erez Braun & Naama Brenner (Israel Institute of Technology)
Marwan W (Science and Technology Research Institute - University of Hertfordshire)
- Reconstructing the regulatory network controlling commitment and sporulation in Physarum polycephalum based on hierarchical Petri Net modelling and simulation (use of Petri nets for GRN)
- Morphomatics (course on Mathematical models for biological pattern formation)
Nic Geard (Complex and Intelligent Systems Group - School of Information Technology and Electrical Engineering - The University of Queensland)
- A gene network model for developing cell lineages
- A Gene Regulatory Network for Cell Differentiation in Caenorhabditis elegans
- Towards more biological mutation operators in gene regulation studies (an artificial genome shows that nucleotide mutations does not fit adding/deleting nodes/edges in a GRN graph)
- Evolving Gene Regulatory Networks for Cellular Morphogenesis
- Structure and dynamics of a gene network model incorporating small RNAs > Modelling the Role of Small RNAs in Gene Regulation
- Dynamics of gene expression in an artificial genome - implications for biological and artificial ontogeny (dynamics of gene expression on an model genome, Reil’99)
- Dynamics of Gene Expression in an Artificial Genome (analysis of stability in GRN generated by artificial genomes)
Jennifer Hallinan (Institute for Molecular Biosciences and School of ITEE - The University of Queensland)
- Towards more relevant evolutionary models: Integrating an artificial genome with a developmental phenotype
Dominique Chu (Computing Laboratory - University of Kent)
- A Category Theoretical Argument agains the Possibility of Artificial Life: Robert Rosen's Central Proof Revisited
Stuart A. Kauffman (University of Pennsylvania, Santa Fe Institute, Universisty of New Mexico)
- Complexity, biomedicine
Christopher G. Langton
- Computational architectures for Artificial Life studies, formal measures of complexity, cellular automata, the role of ecologies in evolution, and the origin of life.
- Computation at the edge of chaos: Phase transitions and emergent computation
- Algorithmic Art . Virtual Creatures
- Computer Graphics. Evolution.
- Prophet works across disciplines on a number of internationally acclaimed projects that have broken new ground in art, technology and science
- Evolutionary Art
Gerald de Jong(Beautiful Code)
- Methods for autonomous adaptation in behavior and morphology of robotic systems
- Biologically-inspired approaches
- Development of intelligent robotics and software inspired by biological principles of self-organization
- Bio-mimetic micro-flying robots
- Evolutionary Software and Hardware
- Collective and Swarm Systems
- Embodied Cognitive Science
- Autonomous agents/mobile robots
- Educational Technology
- Artificial Life
- Morphology/morpho-functional machines
- Situated Design
- Biotic and environmental events that accompanied the Cambrian explosion of multicellular life.
- Director of Nasa’s Astrobiology Institute
- Cellular Automata
- Fine-grained architectures for massively parallel computation
- Connections between microscopic dynamical processes and macroscopic phenomenology. Physical modeling approaches that take advantage of massively parallel, fine-grained computational resources.
- Cellular Automata
- Fine-grained parallelism that is available in nature
- Book: Parallel Computing for Bioinformatics and Computational Biology : Models, Enabling Technologies, and Case Studies
- Public computing grid benefiting humanity
- Computational Grid computing for performance, parallel and distributed systems.
- Models and Modeling Infrastructures for Global Computational Platforms (2005)
- Cluster computing.
- Cellular Automata, tensegrity, domes, alife, …
- A Searchable Database of Alife Related Sites on the Net, Automatically Gathered by an Intelligent Search Bot
- Collection of Alife resources
- The Digital Biology Project: promote and assist in the engineering of complete, biologically-inspired, synthetic ecosystems and organisms
- Graph library for graph-drawing
- A cellular automata programing environment
- A platform for CA and LG (Crystalline Computation)
- A platform for agent-based models.
- A Java-based architecture for the construction of large-scale distributed agent-based applications.
- Multi-agent simulation environment – implemented in Java: cross-platform. Based on hubnet, not so much tested.
- C++ engine for modeling Bayesian networks
- Programmable modeling environment for distributed systems – for students.
- Material on developmental biology