Improving Microscopy-based Resurgent Growth Prediction for Overwintering Cyanobacteria from Harmful Bloom-Impacted Sediments Using Next-Generation Sequencing Coupled with quantitative PCR
收藏NIAID Data Ecosystem2026-05-02 收录
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https://www.ncbi.nlm.nih.gov/sra/SRP576081
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资源简介：
16S sequences from water and sediment that underwent a 14 - day incubation study from 6 source locations. This was done to evaluate the prediction capabilities of using the identification of cyanobacteria in benthic sediment to predict growth potential during bloom season. These sequences contain 16S V4 region sequenced on an Illumina Miseq and full 16S gene region sequenced on an Oxford Nanopore.
创建时间：
2025-05-30
