OpenWorm is an international open science project to simulate the roundworm Caenorhabditis elegans at the cellular level as a simulation. Although the long-term goal is to model all 959 cells of the C. elegans, the first stage is to model the worm's locomotion by simulating the 302 neurons and 95 muscle cells. This bottom up simulation is being pursued by the OpenWorm community. As of this writing, a physics engine called Sibernetic has been built for the project and models of the neural connectome and a muscle cell have been created in NeuroML format. A 3D model of the worm anatomy can be accessed through the web via the OpenWorm browser. The OpenWorm project is also contributing to develop Geppetto, a web-based multi-algorithm, multi-scale simulation platform engineered to support the simulation of the whole organism. OpenWorm is an international open science project to simulate the roundworm Caenorhabditis elegans at the cellular level as a simulation. Although the long-term goal is to model all 959 cells of the C. elegans, the first stage is to model the worm's locomotion by simulating the 302 neurons and 95 muscle cells. This bottom up simulation is being pursued by the OpenWorm community. As of this writing, a physics engine called Sibernetic has been built for the project and models of the neural connectome and a muscle cell have been created in NeuroML format. A 3D model of the worm anatomy can be accessed through the web via the OpenWorm browser. The OpenWorm project is also contributing to develop Geppetto, a web-based multi-algorithm, multi-scale simulation platform engineered to support the simulation of the whole organism. The roundworm Caenorhabditis elegans is a free-living, transparent nematode, about 1 mm in length, that lives in temperate soil environments. It is the type species of its genus. C. elegans has one of the simplest nervous systems of any organism, with its hermaphrodite type having only 302 neurons. Furthermore, the structural connectome of these neurons is fully worked out. There are fewer than one thousand cells in the whole body of a C. elegans worm, and because C. Elegans is a model organism, each has a unique identifier and comprehensive supporting literature. Being a model organism, the genome is fully known, along with many well characterized mutants readily available, a comprehensive literature of behavioural studies, etc. With so few neurons and new calcium 2 photon microscopy techniques it should soon be possible to record the complete neural activity of a living organism. By manipulating the neurons through optogenetic techniques, combined with the above recording capacities the project is in an unprecedented position to be able to fully characterize the neural dynamics of an entire organism. In the process of trying to build an 'in silico' model of a relatively simple organism like C. elegans, new tools are being developed which will make it easier to model progressively more complex organisms. Project Nemaload was created as a research program trying to empirically establish the relevant biological facts which are necessary for a true bottom-up simulation. The project founder, David Dalrymple, is a collaborator on the OpenWorm project. Although the ultimate goal is to simulate all features of C. elegans' behaviour, the project is new and the first behaviour the Open Worm community decided to simulate is a simple motor response: teaching the worm to crawl. To do so, the virtual worm must be placed in a virtual environment. A full feedback loop must be established: Environmental Stimulus > Sensory Transduction > Interneuron Firing > Motor Neuron Firing > Motor Output > Environmental Change > Sensory Transduction. There are two main technical challenges here: modelling the neural/electrical properties of the brain as it processes the information, and modelling the mechanical properties of the body as it moves. The neural properties are being modeled by a Hodgkin-Huxley model, and the mechanical properties are being modeled by a Smoothed Particle Hydrodynamic algorithm. The OpenWorm team built an engine called Geppetto which could integrate these algorithms and due to its modularity will be able to model other biological systems (like digestion) which the team will tackle at a later time. The team also built an environment called NeuroConstruct which is able to output neural structures in NeuroML. Using NeuroConstruct the team reconstructed the full connectome of C. elegans.