Cell type nomenclature for the mammalian brain: Development and application of a systematic, extensible convention

1 code implementation • 9 Jun 2020 • Jeremy A. Miller, Nathan W. Gouwens, Bosiljka Tasic, Forrest Collman, Cindy T. J. van Velthoven, Trygve E. Bakken, Hongkui Zeng, Ed S. Lein, Amy Bernard

The recent advent of single cell RNA-sequencing and other high-throughput technologies has led to an explosion of cell type definitions across multiple organ systems.

Automated Neuron Shape Analysis from Electron Microscopy

no code implementations • 29 May 2020 • Sharmishtaa Seshamani, Leila Elabbady, Casey Schneider-Mizell, Gayathri Mahalingam, Sven Dorkenwald, Agnes Bodor, Thomas Macrina, Daniel Bumbarger, JoAnn Buchanan, Marc Takeno, Wenjing Yin, Derrick Brittain, Russel Torres, Daniel Kapner, Kisuk Lee, Ran Lu, Jinpeng Wu, Nuno daCosta, Clay Reid, Forrest Collman

Morphology based analysis of cell types has been an area of great interest to the neuroscience community for several decades.

Clustering

Label-free prediction of three-dimensional fluorescence images from transmitted-light microscopy

1 code implementation • Nature Methods 2018 • Chawin Ounkomol, Sharmishtaa Seshamani, Mary M. Maleckar, Forrest Collman, Gregory R. Johnson

Understanding cells as integrated systems is central to modern biology.

Image-to-Image Translation

A Community-Developed Open-Source Computational Ecosystem for Big Neuro Data

no code implementations • 9 Apr 2018 • Randal Burns, Eric Perlman, Alex Baden, William Gray Roncal, Ben Falk, Vikram Chandrashekhar, Forrest Collman, Sharmishtaa Seshamani, Jesse Patsolic, Kunal Lillaney, Michael Kazhdan, Robert Hider Jr., Derek Pryor, Jordan Matelsky, Timothy Gion, Priya Manavalan, Brock Wester, Mark Chevillet, Eric T. Trautman, Khaled Khairy, Eric Bridgeford, Dean M. Kleissas, Daniel J. Tward, Ailey K. Crow, Matthew A. Wright, Michael I. Miller, Stephen J. Smith, R. Jacob Vogelstein, Karl Deisseroth, Joshua T. Vogelstein

Big imaging data is becoming more prominent in brain sciences across spatiotemporal scales and phylogenies.

Neurons and Cognition Quantitative Methods

NeuroStorm: Accelerating Brain Science Discovery in the Cloud

no code implementations • 9 Mar 2018 • Gregory Kiar, Robert J. Anderson, Alex Baden, Alexandra Badea, Eric W. Bridgeford, Andrew Champion, Vikram Chandrashekhar, Forrest Collman, Brandon Duderstadt, Alan C. Evans, Florian Engert, Benjamin Falk, Tristan Glatard, William R. Gray Roncal, David N. Kennedy, Jeremy Maitin-Shepard, Ryan A. Marren, Onyeka Nnaemeka, Eric Perlman, Sharmishtaas Seshamani, Eric T. Trautman, Daniel J. Tward, Pedro Antonio Valdés-Sosa, Qing Wang, Michael I. Miller, Randal Burns, Joshua T. Vogelstein

Neuroscientists are now able to acquire data at staggering rates across spatiotemporal scales.

scientific discovery

Probabilistic Fluorescence-Based Synapse Detection

no code implementations • 16 Nov 2016 • Anish K. Simhal, Cecilia Aguerrebere, Forrest Collman, Joshua T. Vogelstein, Kristina D. Micheva, Richard J. Weinberg, Stephen J. Smith, Guillermo Sapiro

The present work describes new probabilistic image analysis methods for single-synapse analysis of synapse populations in both animal and human brains.