Abstract Systems biology has experienced dramatic growth in the number, size, and
complexity of computational models. To reproduce simulation results and reuse models …

To understand complex biological systems requires the integration of experimental and
computational research—in other words a systems biology approach. Computational …

Brian 2 allows scientists to simply and efficiently simulate spiking neural network models.
These models can feature novel dynamical equations, their interactions with the …

A key challenge in neuroscience is the expeditious reconstruction of neuronal circuits. For
model systems such as Drosophila and C. elegans, the limiting step is no longer the …

To facilitate fine-scale phenotyping of whole specimens, we describe here a set of tissue
fixation-embedding, detergent-clearing and staining protocols that can be used to transform …

Abstract BioModels (http://www. ebi. ac. uk/biomodels/) is a repository of mathematical
models of biological processes. A large set of models is curated to verify both …

Neuron modeling may be said to have originated with the Hodgkin and Huxley action
potential model in 1952 and Rall's models of integrative activity of dendrites in 1964. Over …

Biophysical modeling of neuronal networks helps to integrate and interpret rapidly growing
and disparate experimental datasets at multiple scales. The NetPyNE tool (www. netpyne …

Understanding complex biological systems requires extensive support from software tools.
Such tools are needed at each step of a systems biology computational workflow, which …

Background The increasing use of computational simulation experiments to inform modern
biological research creates new challenges to annotate, archive, share and reproduce such …