Integrating CAD and AI Deep Learning, LLMs, LAMs and CRISPR biotech to gain pragmatic-semantic insight into how genomes control natural and designed living, dynamic, developing multicellular systems-including embryos and cancer!
- Deep understanding of living developing embryos and cancer via computer aided design (CAD) and artificial intelligence (AI) using LLMs and LAMs together with biotechnology (CRISPR) genome editing
- Virtual Experiments thousands of times faster than real lab experiments
- Tens of thousands of times faster than typical time of human cell division
- All visual and dynamic multicellular growth
- Genome network dynamics coordinated with cell dynamics
- Full color with sound as cells communicate, divide, push and pull in 5-dimensional space time
- Choice of sounds that cells emit when dividing or sending signals
- Gives a new insight to how humans develop from a single cell
- Shows full visual dynamic cell signaling in 4D space time
- Easy to use:
- Designed for the user with easy visual editing modes
- Direct visual editing modes of developmental networks
- Cut or slice the 3D growing multicellular system and watch it grow – showing the user the inside of the system while it is growing!
- Press Zero ‘0’ to restart growth
- Press Space Bar to start or stop the action
- Cancer Network Genome View gives new deep understanding of how cancer works and how it may be cured
- Gives hope to new types of cancer treatments
- Stop cancer cells by changing the network that controls them
- First in software then in humans
- By applying CRISPR genome editing biotechnology
- Advanced Feature: Generate Genome AI DATA for training LLMs / AI-models to find cancer networks in natural human genomes
- Design a cancer and save the genome as DATA for AI in many randomized versions
- Train the AI model to recognize the cancer networks
- Apply the trained AI-Model to natural genomes to output the regions in the genome that contain the cancer network.
- Use CRISPR like genome editing to edit or remove the cancer network in the real molecular human patients genome.
- Contact: contact (at) cellnomica.com
- Some Publications: