The machine learning technology behind all future crops.
Computomics' machine learning not only answers your toughest plant breeding questions, but empowers you to ask questions you never had the audacity to pose. Computomics’ ⨉SeedScore, Genotyping, and DataScore Technologies provide you with the answers, putting you in control of your plant breeding:
Whether your plant breeding goals are commercial, consumer or environmental, Computomics’ team can help move your program way beyond current limitations of hybrid performance prediction, available land for testing and complex trait planning.
Get the answers you need to accelerate your plant breeding program, today and tomorrow.
We are happy to support you on your way to a new commercial product by providing customized technical support adjusted to your specific plant breeding needs.
Benefit from our machine learning-based regularized kernel methods to predict phenotypes from genome-wide markers. These methods model heterosis and genetic gain. We store the trained predictors to reproducibly analyze next season’s data to make results directly comparable.
We work with you — from desired trait to improved plant. In cooperation with experts in the field of plant gene editing, we offer a full range of services to deliver your desired crop variety. Our comprehensive consultancy applies optimal technologies for your individual goals. We leverage machine learning-based genome analysis to identify the best genome editing targets, then employ a high-quality genome editing service accompanied by extensive quality controls to ensure optimal results. You will gain plant varieties, optimized with your traits of interest, to advance into the commercial pipeline and/or introduce into your breeding programs.
We help you to identify genetic markers for your traits of interest from sequencing data, including single nucleotide polymorphisms (SNPs), insertions and deletions (InDels), copy number variations (CNVs) or structural variants (SVs). By relying on sequencing-based genotyping we ensure an unbiased view of the variance of a population, as it does not rely on previous knowledge.
Depending on your project and specific needs, we set up a tailor-made sequencing-based genotyping pipeline which will take into account optimal sequencing technologies, parameters tuned to arrive at the marker resolution required for your goals and the possibility to impute missing data.
To further increase the accuracy of variant calling, especially for short read data, we can build genome graphs from one or many of these data sources: long read data, assembled contigs or whole genomes, or databases of (structural) variation from your species.
This allows you to:
1. Discover reliable SV markers, even for short read or low-coverage data
2. Reduce or even eliminate reference bias in calling variants
3. Gain access to variation in non-reference genome space
Accuracy will continuously increase with every newly sequenced genome that is incorporated into the pangenome graph. We also offer the advantage of genotyping your (long forgotten) historic material or incorporate it into the graph to collect all the information about your population in one data structure.
Gene editing in plants has become increasingly efficient with the development of CRISPR-based tools. It offers novel possibilities to optimize plant traits in addition to breeding. Genome editing is especially advantageous in this field, as it allows the fast and specific improvement of genes of interest, while protecting traits that have already been carefully bred in any organisms.
We work with you — from desired trait to improved plant: In cooperation with experts in the field of plant gene editing, we offer a full range of services to deliver the desired crop variety. Starting from a comprehensive consultancy on the optimal technologies for your individual goals, machine learning-based genome analysis to identify the best genome editing targets, a high-quality genome editing service, which is accompanied by extensive quality controls.
You will gain plant varieties, optimized with your traits of interest, to advance into the commercial pipeline and/or introduce into your breeding programs.
xSeedScore Information Download
Predict virtual hybrids from a male and female double-haploid population and predict hybrid phenotypes that exceed their parents and testers
Multi-trait optimization in malting barley for specific climates
Advancing rice breeding by predicting actual phenotypic values in specific environments