MOTIVATION: For testing and sensitivity analysis purposes, it is beneficial to have known transcription networks of sufficient size and variability during development of microarray data and network deconvolution algorithms. Description of such networks in a simple language translatable to Systems Biology Markup Language would allow generation of model data for the networks. RESULTS: Described herein is software (RANGE: RAndom Network GEnerator) to generate large random transcription networks in the NEMO (NEtwork MOtif) language. NEMO is recognized by a grammar for transcription network motifs using lex and yacc to output Systems Biology Markup Language models for either specified or randomized gene input functions. These models of known networks may be input to a biochemical simulator, allowing the generation of synthetic microarray data. AVAILABILITY: http://range.sourceforge.net

Ash clouds resulting from volcanic eruptions are a serious hazard to aviation safety. In Alaska alone, there are over 40 active volcanoes whose eruptions may affect more than 40,000 flights using the great circle polar routes each year. The clouds are especially problematic because they are invisible to radar and nearly impossible to distinguish from weather clouds. The Arctic Region Supercomputing Center and the Alaska Volcano Observatory have collaborated to develop a system for predicting and visualizing the movement of volcanic ash clouds when an eruption occurs. The output from the model is combined with a digital elevation model to produce a realistic view of the ash cloud which may be examined interactively from any desired point of view at any time during the prediction period. This paper describes the visualization techniques employed in the system and includes a video animation of the 1989 Mount Redoubt eruption which caused complete engine failure on a 747 passenger jet.>