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Cited by 767

The DOI matches its Crossref record.

Current Protocols in Neuroscience

·2018·Current Protocols in Neuroscience
DOI 10.1002/(issn)1934-8576
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Abstract

Current Protocols in Neuroscience (CPN) draws from techniques in molecular neurobiology, neurophysiology, neuroanatomy, neuropharmacology, and behavioral neuroscience to meet the specific needs of researchers in the full range of disciplines that is involved in studying the brain, nervous system, and corresponding behaviors. The editorial board of CPN have assembled an outstanding range of methods to enable users to explore their fields in greater depth and branch into related areas. The one-volume, looseleaf manual features carefully edited techniques with authors' troubleshooting tips and helpful comments that come from extensive experience in using these procedures. Quarterly updates, filed into the looseleaf, keep you and your laboratory current with the latest developments in this rapidly changing field. The initial purchase includes one year of updates and then subscribers may renew their annual subscriptions. Current Protocols publishes a family of laboratory manuals for bioscientists, including Molecular Biology, Immunology, Human Genetics, Protein Science, Cytometry, Cell Biology, Pharmacology, and Toxicology.

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Citations

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Metadata

Venue
Current Protocols in Neuroscience
Publisher
Wiley
Published
2018-08-06
ISSN
  • 1934-8576 (ISSN-L)
  • 1934-8584
DOI
10.1002/(issn)1934-8576
OpenAlex
W628847457
Cited by
767
References
0
Type
paratext
Language
en
Open access
closed

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CoChat. (2026). Citation check: Current Protocols in Neuroscience. https://app.cochat.ai/papers/10.1002/(issn)1934-8576
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Current Protocols in Neuroscience. (2018). Current Protocols in Neuroscience. https://doi.org/10.1002/(issn)1934-8576

Data sources

Bibliographic data: Semantic Scholar, OpenAlex, Crossref.

Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.