BIN 2.0 Assignment Service
Open access to the Barcode Index Number system. Assign your DNA barcode sequences to putative species clusters without needing a BOLD account.
What is a BIN?
A Barcode Index Number (BIN) is a stable, citable identifier assigned to a cluster of DNA barcode sequences that correspond to a putative species. BINs are computed by comparing sequences against a global reference graph: sequences that fall within a distance threshold are grouped together, and each group receives a persistent formatted identifier such as BOLD:AAA1234.
BINs serve two practical purposes. First, they let you verify taxonomic names: if sequences carrying different species names cluster into a single BIN, or a single species splits across multiple BINs, that requires investigating. Second, they provide species-level identifiers that are independent of taxonomy, making them useful for biodiversity monitoring, environmental DNA analysis, and any workflow where stable identifiers matter more than nomenclatural consensus.
The BIN system was introduced in a 2013 paper that has since accumulated more than 2,000 citations across ecology, systematics, and conservation biology.
Ratnasingham S, Hebert PDN (2013) A DNA-Based Registry for All Animal Species: The Barcode Index Number (BIN) System. PLoS ONE 8(7): e66213. doi:10.1371/journal.pone.0066213
What this service does
This service provides BIN assignments using an updated algorithm that is more scalable, more consistent and better calibrated than the original version. The new algorithm produces assignments that are more stable across dataset additions and better reflect true species boundaries, particularly in groups where the original clustering would over-split.
- Accepts gzip, bzip2, zip, and tar.gz compressed FASTA files
- Supports direct upload and presigned S3 URLs for private data
- Returns a downloadable archive with per-sequence BIN assignments
- Currently supports the COI barcode marker; additional markers are planned
A paper describing the updated algorithm is in preparation. In the meantime, please cite the original BIN paper (Ratnasingham & Hebert 2013, above) in any publication that uses assignments generated by this service.
Access
This is a research tool, not a public API. Access is granted to researchers and institutions with a legitimate scientific purpose. There is no fee.