English
 
Help Privacy Policy Disclaimer
  Advanced SearchBrowse

Item

ITEM ACTIONSEXPORT
Add to Basket
 Local TagsRelease HistoryDetailsSummary
  SyConn2: Dense synaptic connectivity inference for volume electron microscopy

Schubert, P. J., Dorkenwald, S., Januszewski, M., Klimesch, J., Svara, F., Mancu, A., et al. (2022). SyConn2: Dense synaptic connectivity inference for volume electron microscopy. Nature Methods, 19, 1367-1370. doi:10.1038/s41592-022-01624-x.

Item is

 

show all hide all

Basic

show hide
Item Permalink: https://hdl.handle.net/21.11116/0000-000C-0072-3 Version Permalink: https://hdl.handle.net/21.11116/0000-000C-0073-2
Genre: Journal Article

Files

show Files
hide Files
:
s41592-022-01624-x.pdf (Publisher version), 3MB
View   Save
File Permalink:
https://hdl.handle.net/21.11116/0000-000C-0074-1
Name:
s41592-022-01624-x.pdf
Description:
-
OA-Status:
Gold
Visibility:
Public
MIME-Type / Checksum:
application/pdf / [MD5]
Technical Metadata:
View
Copyright Date:
2022
Copyright Info:
© The Author(s) 2022
License:
http://creativecommons.org/licenses/by/4.0/

Locators

show
hide
Locator:
https://www.nature.com/articles/s41592-022-01624-x (Publisher version)
Description:
Brief Communication
OA-Status:
Gold

Creators

show
hide
 Creators:
Schubert, Philipp J.1, 2, Author           
Dorkenwald, Sven1, Author           
Januszewski, Michał3, Author
Klimesch, Jonathan1, Author           
Svara, Fabian4, Author           
Mancu, Andrei2, Author           
Ahmad, Hashir2, Author           
Fee, Michale S.3, Author
Jain, Viren3, Author
Kornfeld, Jörgen2, Author           
Affiliations:
1Department: Electrons-Photons-Neurons / Denk, MPI of Neurobiology, Max Planck Society, ou_1128546              
2Research Group: Circuits of Birdsong / Kornfeld, MPI of Neurobiology, Max Planck Society, ou_3349614              
3External Organizations, ou_persistent22              
4Department of Computational Neuroethology, Max Planck Institute for Neurobiology of Behavior – caesar, Max Planck Society, ou_3361762              

Content

show
hide
Free keywords: -
 Abstract: The ability to acquire ever larger datasets of brain tissue using volume
electron microscopy leads to an increasing demand for the automated
extraction of connectomic information. We introduce SyConn2, an
open-source connectome analysis toolkit, which works with both on-site
high-performance compute environments and rentable cloud computing
clusters. SyConn2 was tested on connectomic datasets with more
than 10 million synapses, provides a web-based visualization interface
and makes these data amenable to complex anatomical and neuronal
connectivity queries.

Details

show
hide
Language(s): eng - English
 Dates: 2022-10-242022-11
 Publication Status: Issued
 Pages: -
 Publishing info: -
 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.1038/s41592-022-01624-x
PMID: 36280715
PMC: PMC9636020
 Degree: -

Event

show

Legal Case

show

Project information

show hide
Project name : -
Grant ID : -
Funding program : RF1 (MH117809-01)
Funding organization : NIH

Source 1

show
hide
Title: Nature Methods
  Abbreviation : Nat Methods
Source Genre: Journal
 Creator(s):
Affiliations:
Publ. Info: New York, NY : Nature Publishing Group
Pages: - Volume / Issue: 19 Sequence Number: - Start / End Page: 1367 - 1370 Identifier: ISSN: 1548-7091
CoNE: https://pure.mpg.de/cone/journals/resource/111088195279556