{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Northcutt AJ"],"funding":["HHS | NIH | National Institute of Mental Health","HHS | NIH | National Institute of General Medical Sciences","NIMH NIH HHS","NINDS NIH HHS","NIGMS NIH HHS"],"pagination":["26980-26990"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC6936480"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["116(52)"],"pubmed_abstract":["Understanding circuit organization depends on identification of cell types. Recent advances in transcriptional profiling methods have enabled classification of cell types by their gene expression. While exceptionally powerful and high throughput, the ground-truth validation of these methods is difficult: If cell type is unknown, how does one assess whether a given analysis accurately captures neuronal identity? To shed light on the capabilities and limitations of solely using transcriptional profiling for cell-type classification, we performed 2 forms of transcriptional profiling-RNA-seq and quantitative RT-PCR, in single, unambiguously identified neurons from 2 small crustacean neuronal networks: The stomatogastric and cardiac ganglia. We then combined our knowledge of cell type with unbi"],"journal":["Proceedings of the National Academy of Sciences of the United States of America"],"pubmed_title":["Molecular profiling of single neurons of known identity in two ganglia from the crab <i>Cancer borealis</i>."],"pmcid":["PMC6936480"],"funding_grant_id":["T32 MH019929","T32 GM008396","R01 MH046742","T32GM008396","R35 NS097343","R25 MH059472","R01MH046742-29"],"pubmed_authors":["Northcutt AJ","Santin JM","Goetz BM","Harris RM","Schulz DJ","Marder E","Otopalik AG","Kick DR","Hofmann HA"],"additional_accession":[]},"is_claimable":false,"name":"Molecular profiling of single neurons of known identity in two ganglia from the crab <i>Cancer borealis</i>.","description":"Understanding circuit organization depends on identification of cell types. Recent advances in transcriptional profiling methods have enabled classification of cell types by their gene expression. While exceptionally powerful and high throughput, the ground-truth validation of these methods is difficult: If cell type is unknown, how does one assess whether a given analysis accurately captures neuronal identity? To shed light on the capabilities and limitations of solely using transcriptional profiling for cell-type classification, we performed 2 forms of transcriptional profiling-RNA-seq and quantitative RT-PCR, in single, unambiguously identified neurons from 2 small crustacean neuronal networks: The stomatogastric and cardiac ganglia. We then combined our knowledge of cell type with unbi","dates":{"release":"2019-01-01T00:00:00Z","publication":"2019 Dec","modification":"2026-05-03T07:55:41.264Z","creation":"2020-05-22T07:00:35Z"},"accession":"S-EPMC6936480","cross_references":{"pubmed":["31806754"],"doi":["10.1073/pnas.1911413116"]}}