Rutger Aldo Vos

The paper presents mitochondrial genomes of Foraminifera and Radiolaria, revealing reduced gene content and a non-canonical genetic code in retarian mitogenomes.

The paper improves bulk segregant analysis by using Gene Ontology to filter flowering time genes in Brassica oleracea, identifying relevant pathways and candidate genes.

The paper develops a deep learning approach for species distribution modeling and applies it to crops and their wild ancestors, showing improved projections for species with many occurrence records.

The paper presents a system that uses computer vision to automate insect counting on sticky traps for assessing meadow bird food supply.

The paper assesses insect availability for meadow bird chicks using image analysis of sticky traps across two years, finding increased insect counts in 2018 but no correlation with management practices.

The paper evaluates using image recognition tools to identify mosquito genera based on wing morphology from digital photographs.

The paper evaluates image analysis methods for classifying Javanese butterflies and slipper orchids, finding that BGR-SURF achieved the best accuracy for butterflies while the original BGR method was best for orchids.

This paper uses deep learning to classify ant species from images, achieving 62-81% top 1 accuracy and 80-92% top 3 accuracy on AntWeb images.

TreeBASEdmp provides a downloadable phylogenetic database and tools for custom analysis, enabling users to query and synthesize phylogenetic data locally.

The paper introduces version 2.0 of Bio::Phylo, a toolkit for phylogenetic data analysis, with improved architecture, speed, and functionality.