meda implements the top 10 analyses/visualizations we recommend for any matrix valued data.
The synapse is the principle active signaling component of the brain's circuitry. As such, tools to visualize, detect, and label synapses would be a useful resource for the neuroscience community. The Open Synaptome Project, a collaboration between NeuroData and the Allen Institute for Brain Science, provides a synaptic analysis toolbox open to the scientific community as well as open access to the array tomography data generated by the Allen Institute.
S. J. Smith. Q & A: Array tomography. BMC Biology, (1)16:98, 2018.
C. Ounkomol, S. Seshamani, M. M. Maleckar, and F. Collman. Label-free prediction of three-dimensional fluorescence images from transmitted light microscopy. bioRxiv:289504, 2018.
A. K. Simhal, B. Gong, J. S. Trimmer, R. J. Weinberg, S. J. Smith, G. Sapiro, and K. D. Micheva. A Computational Synaptic Antibody Characterization and Screening Framework for Array Tomography. bioRxiv, 2018.
G. França and J. T. Vogelstein. Energy Clustering. arXiv, 2017.
A. K. Simhal, C. Aguerrebere, F. Collman, J. T. Vogelstein, K. D. Micheva, R. J. Weinberg, S. J. Smith, and G. Sapiro. Probabilistic fluorescence-based synapse detection. PLoS Computational Biology, 2017.
A. Burette, F. Collman, K. D. Micheva, S. J. Smith, and R. J. Weinberg. Knowing a synapse when you see one. Frontiers in Neuroanatomy, 2015.
F. Collman, J. Buchanan, K. D. Phend, K. D. Micheva, R. J. Weinberg, and S. J. Smith. Mapping Synapses by Conjugate Light-Electron Array Tomography. Journal of Neuroscience, 2015.