The startup develops protein analysis software that utilizes reverse-translation technology to convert peptide sequences into DNA, enabling single-molecule protein sequencing. This platform provides researchers with complete proteome information at scale, facilitating more efficient protein sample analysis.
Funding
$169M raised to dateRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Founders
Product
Problem
Current proteomic research is limited by difficulties in scaling studies, hindering the comprehensive analysis of proteins needed to understand complex biological processes and diseases. Traditional methods lack the throughput and scale of modern genomics, impeding advancements in personalized medicine and multiomic research.
Solution
Encodia's ProteoCode™ technology addresses this limitation by reverse-translating peptide sequences into DNA libraries, enabling protein sequencing at a scale comparable to next-generation sequencing (NGS). This approach uses affinity reagent binders with DNA barcode tags to identify amino acids within peptides, creating a library of billions of elements for in-depth protein analysis. The resulting data integrates with multiomic approaches, providing researchers with comprehensive insights into cellular processes and accelerating discoveries in human health. By scaling proteomic studies, Encodia facilitates a deeper understanding of biology and enables personalized medicine approaches.
Target Audience
The primary target audience includes researchers and scientists in the fields of proteomics, genomics, personalized medicine, and multiomics, as well as pharmaceutical and biotechnology companies.
Features
- Reverse-translation of peptide sequences into DNA libraries for high-throughput protein sequencing.
- Compatibility with next-generation sequencing (NGS) platforms for scalable analysis.
- Affinity reagent binders with DNA barcode tags for amino acid identification.
- Ability to create billions of library elements, each identifying an amino acid in the peptide.
- Integration with multiomic data analysis pipelines.