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Wenhui Song

Publications -  7
Citations -  2339

Wenhui Song is an academic researcher. The author has contributed to research in topics: Phylogenomics & Gene. The author has an hindex of 5, co-authored 7 publications receiving 1943 citations.

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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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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.

Phylogenomics Resolves The Timing And Pattern Of Insect Evolution: Supplementary File Archives.

TL;DR: A phylogenetic analysis of protein-coding genes from all major insect orders and close relatives was performed by Misof et al. as discussed by the authors, who used this resolved phylogenetic tree together with fossil analysis to date the origin of insects to ~479 million years ago and to resolve longcontroversial subjects in insect phylogeny.
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Positive and relaxed selection associated with flight evolution and loss in insect transcriptomes.

TL;DR: Some convergence in gene-specific selection pressures associated with flight ability is supported, and the exploratory analysis provided some new insights into gene categories potentially associated with the gain and loss of flight in insects.
Journal ArticleDOI

Characterization of viral RNA splicing using whole-transcriptome datasets from host species.

TL;DR: A novel approach to characterizing viral AS using whole transcriptome dataset from host species and when applied to large-scale transcriptomics projects with diverse taxonomic sampling is expected to rapidly expand knowledge on RNA splicing mechanisms for a wide range of viruses.