Gene embeddings used in GenePT: A Simple But Hard-to-Beat Foundation Model for Genes and Cells Built From ChatGPT

These are the pulled NCBI (and UniProt, when applicable) summaries of genes, as well as the corresponding OpenAI text embeddings (text-embedding-ada-002 and text-embedding-3-large) computed on the summaries. See methods details in Chen and Zou (2024+).

The unzipped folder contains four different files: 

NCBI_summary_of_genes.json (NCBI gene card summary of human genes)

NCBI_UniProt_summary_of_genes.json (NCBI gene card and UniProt protein (when applicable) summary of human genes)

GenePT_gene_embedding_ada_text.pickle (a dictionary of numpy array where gene names (upper case) are keys and text-embedding-ada-002 embeddings of the summary in 1. are the values)

GenePT_gene_protein_embedding_model_3_text.pickle (a dictionary of numpy array where gene names (upper case) are keys and text-embedding-3-large embeddings of the summary in 1. are the values)

Reference:

Chen YT, Zou J. (2024+) GenePT: A Simple But Effective Foundation Model for Genes and Cells Built From ChatGPT. bioRxiv preprint: https://www.biorxiv.org/content/10.1101/2023.10.16.562533v1.