Lab automation

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

To interconnect different knowledge domains, we use different semantic web technologies.

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

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

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

High performance BLAST implementation adapted to run in Spark clusters.

Discovery of markers in all plant species by next-generation sequencing for accelerated plant breeding

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

Genomic selection (GS) accelerates achieving genetic gain through shorter breeding cycles and is an alternative to marker-assisted selection. Genetwister implements new breeding schemes and methods that integrate GS for crop improvement.

With increasing sample numbers and marker panel sizes, it is valuable to increase the throughput of sequencing and genotyping procedures. Genetwister develops cost-effective methods and applies available methods for allowing high-throughput genomics.