Some doubts about downstream tasks about hyena-dna HOT 4 CLOSED

Not sure what you mean DNA tokenization as a task. We just treat every character as a token (ie the smallest unit of data fed into the model) here, so there's nothing to learn.

from hyena-dna.

Not sure what you mean DNA tokenization as a task. We just treat every character as a token (ie the smallest unit of data fed into the model) here, so there's nothing to learn.

Sorry for my unclear expression！

“DNA tokenization” means segment DNA sequence into some words . For example , in English , we segment "howareyou" into "how"、 “are" 、 ”you" . In terms of DNA , we segment "AGCTAGCT" into "AGC" 、"TAGCT", 2 wrods .

I want to break long DNA sequence into meaningful words , in order to find the secrect of non-coding regions of DNA.

i already know what you mean for "treat every character as a token". But i am still not sure whether your model can fit this specific task?

from hyena-dna.

People usually use byte pair encoding tokenizers to learn meaningful aggregating of characters (in natural language). It's based on frequency of the subwords though, not semantics.

I don't know how you would do that here. I'm guessing there are DNA motif finding algorithms, but I wouldn't know where to begin, sorry.

from hyena-dna.

People usually use byte pair encoding tokenizers to learn meaningful aggregating of characters (in natural language). It's based on frequency of the subwords though, not semantics.

I don't know how you would do that here. I'm guessing there are DNA motif finding algorithms, but I wouldn't know where to begin, sorry.

ok，thanks for your time and patient again！ I will explore more about this repo and other methods.

thanks again！

from hyena-dna.