Protein language model embeddings improve sORF coding prediction — ARCADIA Knowledge Graph

InferenceChain·arcadia

Protein language model embeddings improve sORF coding prediction

Reasoning chain explaining how embeddings from protein language models provide latent information that improves the classification of coding versus non-coding transcripts, especially for short open reading frames (sORFs).

Confidence
100%
◑provedactivecomplexity: low

Reasoning Steps (3)

Embeddings encode latent coding propensityStep 1
Improved accuracy on short sequencesStep 2
Package enhances usability and expansionStep 3

Source

Using protein language models to predict coding and non-coding transcripts with plm-utils