gene-database

Batch lookup of NCBI gene metadata is performed by running the batch_gene_lookup.py script with a file of gene symbols and a target organism. The script queries E-utilities and the Datasets API to generate a structured JSON annotation report.

Yes, cross-species queries and organism filters support retrieving GO annotations, chromosomal locations, and transcripts for human and model organisms. This enables comparative genomics, pathway analysis, and gene panel construction across different species.

The best way to annotate large gene lists is using batch lookups that query NCBI ESearch, ESummary, and EFetch endpoints. This assembles IDs, descriptions, and GO annotations into structured JSON suitable for enriching downstream bioinformatics workflows.

Querying NCBI E-utilities and the Datasets API requires access to the endpoints and explicitly handles rate limits. This ensures stable data retrieval when assembling gene annotations or performing large batch lookups across multiple organisms.

Find gene IDs by searching genes by symbol or ID across organisms using NCBI ESearch and EFetch. This centralizes data retrieval from disparate sources, enabling researchers to quickly locate gene IDs and retrieve current metadata for cross-species comparisons.

Structured JSON is used for gene annotation tasks because it standardizes the output of batch lookups and cross-species queries. This format ensures that retrieved metadata, transcripts, and GO annotations are directly suitable for downstream processing in pathway analyses.