Experimental Design

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

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.

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

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

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.

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

CROPaware – A web based software platform for breeding and genomics data management.
Leafy - Our state-of-the-art lead dicovery platform.

High performance BLAST implementation adapted to run in Spark clusters.

Using state-of-the-art long read sequencing technologies, Genetwister builds high quality genome assemblies of novel species and obtains long-range genomic information such as haplotypes and structural variants.

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