Datasheet-Detroit Lake-OR

공공데이터포털

The data include the abundance and community compositions characterized using qPCR and metagenomic sequences. This dataset is associated with the following publication: Jeon, Y., I. Struewing, K. Clauson, N. Reetz, N. Fairchild, L. Goeres-Priest, T. Dreher, R. Labiosa, K. Carpenter, B. Rosen, E. Villegas, and J. Lu. Dominant Dolichospermum and microcystin production in Detroit Lake (Oregon, USA). Harmful Algae. Elsevier B.V., Amsterdam, NETHERLANDS, 142: 102802, (2025).

River-cyanobacteria-datasets

공공데이터포털

Sequence data are used for cyanobacterial community and toxic species analysis. This dataset is associated with the following publication: Linz, D., N. Sienkiewicz, I. Struewing, E.A. Stelzer, J.L. Graham, and J. Lu. Metagenomic mapping of cyanobacteria and potential cyanotoxin producing taxa in large rivers of the United States. Scientific Reports. Nature Publishing Group, London, UK, 13: 2806, (2023).

River-cyanobacteria-datasets

공공데이터포털

Sequence data are used for cyanobacterial community and toxic species analysis. This dataset is associated with the following publication: Linz, D., N. Sienkiewicz, I. Struewing, E.A. Stelzer, J.L. Graham, and J. Lu. Metagenomic mapping of cyanobacteria and potential cyanotoxin producing taxa in large rivers of the United States. Scientific Reports. Nature Publishing Group, London, UK, 13: 2806, (2023).

Phtoplankton qPCR Dataset

공공데이터포털

The dataset including qPCR, phytoplankton counts and water quality parameters are used for the evaluation of phytoplankton identification and quantification and assessment of eutrophication. This dataset is associated with the following publication: Zhang, C., K. McIntosh, N. Sienkiewicz, E.A. Stelzer, J.L. Graham, and J. Lu. Using cyanobacteria and other phytoplankton to assess trophic conditions: A qPCR-based, multi-year study in twelve large rivers across the United States. WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 235: 119679, (2023).

Phtoplankton qPCR Dataset

공공데이터포털

The dataset including qPCR, phytoplankton counts and water quality parameters are used for the evaluation of phytoplankton identification and quantification and assessment of eutrophication. This dataset is associated with the following publication: Zhang, C., K. McIntosh, N. Sienkiewicz, E.A. Stelzer, J.L. Graham, and J. Lu. Using cyanobacteria and other phytoplankton to assess trophic conditions: A qPCR-based, multi-year study in twelve large rivers across the United States. WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 235: 119679, (2023).

Use of qPCR and RT-qPCR for Monitoring Variations of Microcystin Producers and Early Warning Their Toxin Production in an Ohio Inland Lake

공공데이터포털

qPCR and RT-qPCR. This dataset is associated with the following publication: Lu, J., I. Struewing, L. Wymer, D. Tettenhorst, J. Shoemaker, and J. Allen. Use of qPCR and RT-qPCR for monitoring variations of microcystin producers and as an early warning system to predict toxin production in an Ohio inland lake. WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 170: 115262, (2020).

Use of qPCR and RT-qPCR for Monitoring Variations of Microcystin Producers and Early Warning Their Toxin Production in an Ohio Inland Lake

공공데이터포털

qPCR and RT-qPCR. This dataset is associated with the following publication: Lu, J., I. Struewing, L. Wymer, D. Tettenhorst, J. Shoemaker, and J. Allen. Use of qPCR and RT-qPCR for monitoring variations of microcystin producers and as an early warning system to predict toxin production in an Ohio inland lake. WATER RESEARCH. Elsevier Science Ltd, New York, NY, USA, 170: 115262, (2020).

River-Chla-qPCR dataset

공공데이터포털

This dataset is the evaluation of eutrophication in rivers based on quantitative polymerase chain reactions (qPCRs) of phytoplankton. The qPCR data of 2017, 2018, and 2019 are included in the current dataset. The 2917, 2018, and 2019 physicochemical and biological data generated by the USGS are also included in the current file. This dataset is associated with the following publication: Zhang, C., K. McIntosh, N. Sienkiewicz, E.A. Stelzer, J.L. Graham, and J. Lu. qPCR-based phytoplankton abundance and chlorophyll a: A multi-year study in twelve large freshwater rivers across the United States. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 954: 175067, (2024).

2016 Harsha EPA Dataset

공공데이터포털

(1) qPCR and RT-qPCR for cyanotoxin producing genes, and (2) some water quality parameters. This dataset is associated with the following publication: Duan, X., C. Zhang, I. Struewing, X. Li, H. Allen, and J. Lu. Cyanotoxin-encoding genes as powerful predictors of cyanotoxin production during harmful cyanobacterial blooms in an inland freshwater lake: Evaluating a novel early-warning system. SCIENCE OF THE TOTAL ENVIRONMENT. Elsevier BV, AMSTERDAM, NETHERLANDS, 830: 154568, (2022).

AndersonLake datasets

공공데이터포털

The data include sequences, qPCR, RT-qPCR, water nutrients and cyanotoxins.