My gut says protein-protein interactions aren’t that useful given how these interactions scale, and on top of that you have post-translational modifications, SNVs etc. It’s a very very hard problem to solve.

Instead, we can focus on gene-gene interactions and go bottom up. There, we don’t need new wetlab techniques that needs to be validated, measure mRNA instead. Plus, an average single cell contains 40 million proteins, yet the number of mRNA molecules are orders of magnitudes less and can be sequenced with high precision.

If you for instance open KEGG database in graph mode, you will see one of the largest manually curated datasets ever. Yet it is still tiny! If you imagine A,T,G,C as alphabet, and genes as special tokens. All we know as humanity is couple of words… and it’s sad.

I think LLMs might be our best bet on these. Given few words they might uncover “new words” we have never thought about. I kinda tried this… but the methodology is still shaky.

https://celvox.co/blog/TCC/index.html