Semantic Web

Improved genomic selection and breeding utilizing high quality reference genomes

Genomic selection (GS) is an alternative to marker-assisted selection, which can accelerate the genetic gain through shorter breeding cycles. Genetwister is implementing new breeding schemes and methods that integrate GS for crop improvement.

At Genetwister, tools are developed using distributed computing models and technologies like Spark and Hadoop.

Genetwister investigates new methods to integrate phenotypic data into genetic models to support breeding

Tailored marker selection allowing for genotyping regardless of species, genome size and ploidy level.

High parallel computing version of a sequence alignment application.

Acceleration and cost reduction in plant breeding with improved genotype/phenotype relations, utilizing linked variants.

With increasing sample numbers comes the need for automating the most valuable and applied protocols at Genetwister.

With the increasing demands for DNA molecule size and purity on the newest long read sequencing platforms, comes the need for developing new protocols for DNA isolation from different biological sources in the laboratory at Genetwister.

Advanced statistical models are needed to increase the power to discover (new) associations between genetic and phenotypic variation