Christoph Mayer

This study evaluates de novo transcriptome assemblers and quantification tools for non-model arthropods, finding that Trinity and rnaSPAdes outperform IDBA-tran, and Salmon provides faster and more sensitive quantification than RSEM.

Ali-U-Net is a convolutional transformer neural network that aligns DNA sequences more accurately and faster than existing tools in specific scenarios.

This study uses phylogenomic data to reconstruct the evolutionary history of caddisflies, finding that portable case-making evolved independently in three lineages.

The paper shows that nuclear-encoded universal single-copy orthologs (USCOs) outperform mitochondrial DNA barcoding in species discrimination and taxonomic assignment across metazoans.

This paper introduces the λ statistic to evaluate the reliability of molecular divergence time estimates using empirical fossilization rates and applies it to beetle and insect data.