Comment by kylehotchkiss
Comment by kylehotchkiss 18 hours ago
Fascinating platform. I'm fairly new in my bio education but are you effectively finding sequences on NIH and then intelligently chaining them together?
I had some fun one evening asking Claude how I could string together sequences for an imaginary therapeutic and it gave me enough to put into alphafold and get a render :) (Worst therapeutic ever: deliver mRNA into macrophages to target those pesky bacteria who happily just choose to reside there)
Also: How do you plan to navigate the unfortunate part of our country trying to write mRNA out of the American vocabulary?
> finding sequences on NIH
Almost! Yes most of the data is on NIH sub-institutes. For us we take most of the data from NCBI and intelligently pair it together. The training objective of our model takes pairs of sequences (thus the Joint Embedding Architecture) and trains the model to recognize that they are semantically similar but differ in appearance. This is conceptually similar to a lot of the contrastive learning literature from computer vision.
Sounds like a fun side project :)
There are some great tools out there for putting together plasmids for gene therapies where you can plug in different "elements". Promoters UTRs payloads - check out SnapGene I believe they have a free version.
I personally am hopeful that the political headwinds will blow over. When it comes to cancer vaccines it's one of the most exciting new modalities for treating cancer.
1 in 2 Americans are going to get cancer in their lifetime so no matter political affiliation, the need for health will ultimately drive people to invest in the modality.