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915 results for “metagenomics”
Supplementary material 1 from: Swenson SJ, Eichler L, Hörren T, Kolter A, Köthe S, Lehmann GUC, Meinel G, Mühlethaler R, Sorg M, Gemeinholzer B (2022) The potential of metabarcoding plant components of Malaise trap samples to enhance knowledge of plant-insect interactions. Metabarcoding and Metagenomics 6: e85213. https://doi.org/10.3897/mbmg.6.85213
Table S1
Sample sheet metagenomics
<p>Sample sheet metagenomics</p>
Supplementary material 2 from: Martin JL, Santi I, Pitta P, John U, Gypens N (2022) Towards quantitative metabarcoding of eukaryotic plankton: an approach to improve 18S rRNA gene copy number bias. Metabarcoding and Metagenomics 6: e85794. https://doi.org/10.3897/mbmg.6.85794
Supplementary Data 2
Supplementary material 1 from: Martin JL, Santi I, Pitta P, John U, Gypens N (2022) Towards quantitative metabarcoding of eukaryotic plankton: an approach to improve 18S rRNA gene copy number bias. Metabarcoding and Metagenomics 6: e85794. https://doi.org/10.3897/mbmg.6.85794
Supplementary Data 1
Supplementary material 3 from: Martin JL, Santi I, Pitta P, John U, Gypens N (2022) Towards quantitative metabarcoding of eukaryotic plankton: an approach to improve 18S rRNA gene copy number bias. Metabarcoding and Metagenomics 6: e85794. https://doi.org/10.3897/mbmg.6.85794
Supplementary Data 3
Supplementary material 4 from: Martin JL, Santi I, Pitta P, John U, Gypens N (2022) Towards quantitative metabarcoding of eukaryotic plankton: an approach to improve 18S rRNA gene copy number bias. Metabarcoding and Metagenomics 6: e85794. https://doi.org/10.3897/mbmg.6.85794
Tables S1–S4, Figures S1–S4
Supplementary material 2 from: Sildever S, Nishi N, Inaba N, Asakura T, Kikuchi J, Asano Y, Kobayashi T, Gojobori T, Nagai S (2022) Monitoring harmful microalgal species and their appearance in Tokyo Bay, Japan, using metabarcoding. Metabarcoding and Metagenomics 6: e79471. https://doi.org/10.3897/mbmg.6.79471
Tables S1–S13
Supplementary material 1 from: Sildever S, Nishi N, Inaba N, Asakura T, Kikuchi J, Asano Y, Kobayashi T, Gojobori T, Nagai S (2022) Monitoring harmful microalgal species and their appearance in Tokyo Bay, Japan, using metabarcoding. Metabarcoding and Metagenomics 6: e79471. https://doi.org/10.3897/mbmg.6.79471
Figures S1–S6
Supplementary material 1 from: Inoue N, Sato M, Furuichi N, Imaizumi T, Ushio M (2022) The relationship between eDNA density distribution and current fields around an artificial reef in the waters of Tateyama Bay, Japan. Metabarcoding and Metagenomics 6: e87415. https://doi.org/10.3897/mbmg.6.87415
Tables S1–S4
Supplementary material 1 from: Moore MA, Scheible MK, Robertson JB, Meiklejohn KA (2022) Assessing the lysis of diverse pollen from bulk environmental samples for DNA metabarcoding. Metabarcoding and Metagenomics 6: e89753. https://doi.org/10.3897/mbmg.6.89753
Table S1
Supplementary material 2 from: Inoue N, Sato M, Furuichi N, Imaizumi T, Ushio M (2022) The relationship between eDNA density distribution and current fields around an artificial reef in the waters of Tateyama Bay, Japan. Metabarcoding and Metagenomics 6: e87415. https://doi.org/10.3897/mbmg.6.87415
Figures S1–S4
Supplementary material 2 from: Moore MA, Scheible MK, Robertson JB, Meiklejohn KA (2022) Assessing the lysis of diverse pollen from bulk environmental samples for DNA metabarcoding. Metabarcoding and Metagenomics 6: e89753. https://doi.org/10.3897/mbmg.6.89753
Table S2
Supplementary Material for Metagenomic Thermomter
<p>These data are supplementary data for "Metagenomic Thermometer"</p>
Supplementary material 5 from: Tedersoo L, Anslan S, Bahram M, Põlme S, Riit T, Liiv I, Kõljalg U, Kisand V, Nilsson RH, Hildebrand F, Bork P, Abarenkov K (2015) Shotgun metagenomes and multiple primer pair-barcode combinations of amplicons reveal biases in metabarcoding analyses of fungi. MycoKeys 10: 1-43. https://doi.org/10.3897/mycokeys.10.4852
Table S5. Data set of the ITS2 barcode.: Explanation note: Data set of the ITS2 barcode.
Supplementary material 4 from: Tedersoo L, Anslan S, Bahram M, Põlme S, Riit T, Liiv I, Kõljalg U, Kisand V, Nilsson RH, Hildebrand F, Bork P, Abarenkov K (2015) Shotgun metagenomes and multiple primer pair-barcode combinations of amplicons reveal biases in metabarcoding analyses of fungi. MycoKeys 10: 1-43. https://doi.org/10.3897/mycokeys.10.4852
Table S4. Data set of the ITS1 barcode.: Explanation note: Data set of the ITS1 barcode.
Supplementary material 3 from: Vamos E, Elbrecht V, Leese F (2017) Short COI markers for freshwater macroinvertebrate metabarcoding. Metabarcoding and Metagenomics 1: e14625. https://doi.org/10.3897/mbmg.1.14625
Overview of similarity of used inline tags for the fwh1 and fwh2 fusion primers.
Supplementary material 2 from: Vamos E, Elbrecht V, Leese F (2017) Short COI markers for freshwater macroinvertebrate metabarcoding. Metabarcoding and Metagenomics 1: e14625. https://doi.org/10.3897/mbmg.1.14625
Developed fusion primers for fwh1 and fwh2 on the Illumina high throughput sequencing platform.
Supplementary material 11 from: Vamos E, Elbrecht V, Leese F (2017) Short COI markers for freshwater macroinvertebrate metabarcoding. Metabarcoding and Metagenomics 1: e14625. https://doi.org/10.3897/mbmg.1.14625
Proportion of shared reads between the two replicates for DceM amplified with the fwh1 primer set.
Supplementary material 10 from: Vamos E, Elbrecht V, Leese F (2017) Short COI markers for freshwater macroinvertebrate metabarcoding. Metabarcoding and Metagenomics 1: e14625. https://doi.org/10.3897/mbmg.1.14625
OTU table for the 52 taxa mock samples sequenced with the fwh1 and fwh2 primer set.
Supplementary material 1 from: Vamos E, Elbrecht V, Leese F (2017) Short COI markers for freshwater macroinvertebrate metabarcoding. Metabarcoding and Metagenomics 1: e14625. https://doi.org/10.3897/mbmg.1.14625
Primers evaluated in this study
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
Annotated Behaviour and Observability Dataset (ABODe)
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.