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Min Tang

Researcher at China Agricultural University

Publications -  22
Citations -  3090

Min Tang is an academic researcher from China Agricultural University. The author has contributed to research in topics: Metagenomics & Biology. The author has an hindex of 11, co-authored 19 publications receiving 2568 citations. Previous affiliations of Min Tang include Nanjing Agricultural University.

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Journal ArticleDOI

Phylogenomics resolves the timing and pattern of insect evolution

Bernhard Misof, +105 more
- 07 Nov 2014 - 
TL;DR: The phylogeny of all major insect lineages reveals how and when insects diversified and provides a comprehensive reliable scaffold for future comparative analyses of evolutionary innovations among insects.
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Ultra-deep sequencing enables high-fidelity recovery of biodiversity for bulk arthropod samples without PCR amplification

TL;DR: The ability of the new Illumina PCR-free pipeline for DNA metabarcoding to detect small arthropod specimens and its tendency to avoid most, if not all, false positives suggests its great potential in biodiversity-related surveillance, such as in biomonitoring programs.
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Multiplex sequencing of pooled mitochondrial genomes—a crucial step toward biodiversity analysis using mito-metagenomics

TL;DR: A novel multiplex sequencing and assembly pipeline allowing for simultaneous acquisition of full mitogenomes from pooled animals without DNA enrichment or amplification is developed and demonstrates the plausibility of a multi-locus mito-metagenomics approach as the next phase of the current single- locus metabarcoding method.
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High-throughput monitoring of wild bee diversity and abundance via mitogenomics

TL;DR: It is shown that the metagenomic mining and resequencing of mitochondrial genomes (mitogenomics) can be applied successfully to bulk samples of wild bees, and species lists, biomass frequencies, extrapolated species richness and community structure were recovered with less error than in a metabarcoding pipeline.
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Performance of amplicon and shotgun sequencing for accurate biomass estimation in invertebrate community samples.

TL;DR: Overall, mitogenomic sequencing yielded more informative predictions of biomass content from bulk macroinvertebrate communities than metabarcoding, but for large‐scale ecological studies, metabarcode currently remains the most commonly used approach for diversity assessment.