Indigenous species barcode database improves the identification of zooplankton.

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Bibliographic Details
Title: Indigenous species barcode database improves the identification of zooplankton.
Authors: Yang J; State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing, P. R. China., Zhang X; State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing, P. R. China., Zhang W; State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing, P. R. China., Sun J; State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing, P. R. China., Xie Y; State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing, P. R. China., Zhang Y; Nanjing Institute of Environmental Sciences, Ministry of Environmental Protection, Nanjing, China., Burton GA Jr; School for Environment and Sustainability, University of Michigan, Ann Arbor, MI, United States of America., Yu H; State Key Laboratory of Pollution Control & Resource Reuse, School of the Environment, Nanjing University, Nanjing, P. R. China.
Source: PloS one [PLoS One] 2017 Oct 04; Vol. 12 (10), pp. e0185697. Date of Electronic Publication: 2017 Oct 04 (Print Publication: 2017).
Publication Type: Journal Article
Journal Info: Publisher: Public Library of Science Country of Publication: United States NLM ID: 101285081 Publication Model: eCollection Cited Medium: Internet ISSN: 1932-6203 (Electronic) Linking ISSN: 19326203 NLM ISO Abbreviation: PLoS One Subsets: MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1932-6203
DOI:10.1371/journal.pone.0185697