DNAI group

🧬 The first comprehensive benchmark of genomic foundation models is here

Can AI really understand DNA well enough to detect cancer-related signals?

A new study compares leading genomic foundation models on detecting gene fusion breakpoints — a key biomarker in oncology.

The results are striking:
⚡ up to 96.7% accuracy
📉 significantly less training data needed
🚀 outperforming traditional deep learning approaches

👉 Read the full article: https://lnkd.in/dp27pVyu

👏 We’re especially proud that this work was driven by our amazing colleagues Radim Krupicka and Bohuslav Dvorský, together with the team. DNAi contributed by providing consultation and infrastructure — it was a pleasure to be part of this research.

🔬 At DNAi, through Floxgen, we continuously support the genomics research community by making large-scale data processing more accessible, scalable, and efficient.

💡 The development of Floxgen is partially co-funded by the European Union and the Ministry of Industry and Trade of the Czech Republic under the project “FloxgenAI: A Platform for the Safe and Standardized Deployment of Foundation Models in Human Genome Analysis”.

🧬 Floxgen Aggregator is now available on Azure Marketplace

Genomic data holds enormous potential — but working with it is still
complex, costly, and time-consuming.

Floxgen Aggregator simplifies it.

It is a secure and scalable platform for automated genomic data aggregation and population-level analysis — without the need to build and maintain complex bioinformatics infrastructure.

What does it enable in practice?
🔄 automated ingestion and aggregation of genomic variant data
📊 population-level statistics and variant frequency analysis
⚡ high-performance search across large genomic datasets
🛡️ secure, privacy-preserving data processing
🔗 seamless integration via web interface and APIs

By automating complex genomic workflows, Floxgen reduces operational overhead and accelerates time to insight.

👉 Get it on Azure Marketplace: https://lnkd.in/d4MhcPE2

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