Computational crop modelling
The platform combines graph machine-learning-based in silico modelling with in vivo validation to identify genomic modifications for traits in any crop.
Source: LinkedIn company description · Retrieved October 13, 2026
Biographica uses gene-editing, high-throughput sequencing, and biology-aware machine learning in its crop-improvement work.
Its platform combines graph machine-learning modelling with in vivo validation to identify genomic modifications for crop traits. The company identifies choosing genes to edit and how to edit them as a bottleneck in crop improvement.
Based on the company’s public LinkedIn information, supplied through RevenueBase.
The platform combines graph machine-learning-based in silico modelling with in vivo validation to identify genomic modifications for traits in any crop.
Source: LinkedIn company description · Retrieved October 13, 2026
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RevenueBase prepared this profile from the company’s public LinkedIn information and RevenueBase company data. These source records were retrieved on October 13, 2026. AI helped summarize these sources, with a separate automated check against the source text completed on November 3, 2026. Directory positions use company-contact counts from separate saved list snapshots dated September 5, 2026, September 14, 2026, September 15, 2026, September 17, 2026, September 18, 2026, September 19, 2026, September 21, 2026, September 22, 2026, September 29, 2026 and October 7, 2026. How the company lists are built.
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