Distributed Analysis Computing
Distributed Analysis Computing
At Genetwister, tools are developed using distributed computing models and technologies like Spark and Hadoop.
At Genetwister, tools are developed using distributed computing models and technologies like Spark and Hadoop.
To interconnect different knowledge domains, we use different semantic web technologies.
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.
CROPaware – A web based software platform for breeding and genomics data management.
Leafy - Our state-of-the-art lead dicovery platform.
Discovery of markers in all plant species by next-generation sequencing for accelerated plant breeding
Advanced statistical models are needed to increase the power to discover (new) associations between genetic and phenotypic variation.
Acceleration and cost reduction in plant breeding with improved genotype/phenotype relations, utilizing linked variants.
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.
High performance BLAST implementation adapted to run in Spark clusters.