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Switzerland Omics

We build statistical tools that make genomic medicine reliable — combining deep technology with thoughtful, beautiful design.

Our mission is to transform uncertainty in genomic data into evidence that clinicians, researchers, and public health systems can trust. We believe that true progress happens where rigorous science meets clear, elegant communication. Beautiful design is not decoration for us — it's how complex ideas become understandable and usable.

What We Stand For

  • Simplicity
    Complexity deserves clarity. Our tools distil advanced statistical methods into results anyone can interpret.

  • Technical Depth
    We solve hard genomic problems without compromise, always prioritising correctness over convenience.

  • Design as Function
    We treat visual design as part of the technology itself. It’s not aesthetic for its own sake, but the path to insight.

  • Accountability
    We believe in evidence that can be traced, tested, and reproduced.

Our Work

  • Statistical models for interpreting genomic data
  • Tools for calculating probabilities and credible intervals in genetic diagnostics
  • Software pipelines for clean, reproducible analyses
  • Visual and report outputs where clarity and aesthetic quality go hand in hand

We are not optimising for trends. We are building the statistical and design infrastructure for the next decade of genomic medicine.


Switzerland Omics
www.switzerlandomics.ch
admin@switzerlandomics.ch

Popular repositories Loading

  1. .github .github Public

  2. docs-switzerlandomics.github.io docs-switzerlandomics.github.io Public

    Dev docs

    HTML

  3. src-min_char_rnn_r src-min_char_rnn_r Public

    A character-level recurrent neural network implemented from first principles in R. Demonstrates how it learns, validates predictions and generates text on a laptop CPU.

    R

  4. src-min_char_transformer_r src-min_char_transformer_r Public

    A small, GPT-like, decoder-style character Transformer with one attention block written directly in R.

    R

  5. src-min_gpt2_r src-min_gpt2_r Public

    A small GPT-2-style language model decoder-only Transformer built directly in R from scratch. Runs on CPU.

    R

  6. ai-fast_mm_search ai-fast_mm_search Public

    Python

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