GenBank to FASTA Converter
Convert GenBank format files to clean FASTA format instantly. Perfect for bioinformatics workflows.
GenBank Input
FASTA Output
Understanding GenBank and FASTA Formats
GenBank Format
- • Rich annotation format from NCBI
- • Contains sequence + metadata
- • Includes features, references, taxonomy
- • Standard for database submissions
- • Human-readable but verbose
FASTA Format
- • Simple sequence-only format
- • Header line starts with ">"
- • Followed by sequence data
- • Widely supported by analysis tools
- • Compact and easy to parse
When to Convert GenBank to FASTA
Common Use Cases:
- • BLAST searches
- • Multiple sequence alignment
- • Phylogenetic analysis
- • Custom analysis scripts
Benefits:
- • Smaller file sizes
- • Faster processing
- • Universal compatibility
- • Easier parsing
How the Conversion Works
GenBank and FASTA are two of the most common ways to store biological sequences, but they serve different purposes. A GenBank record (the flat-file format distributed by NCBI) is richly annotated: it opens with a LOCUS line, then carries metadata such as DEFINITION, ACCESSION, VERSION, SOURCE and ORGANISM, a FEATURES table describing genes, coding regions and other elements, literature REFERENCES, and finally the ORIGIN block containing the sequence itself, printed in numbered blocks of ten bases. FASTA, by contrast, is deliberately minimal: a single header line beginning with a greater-than sign, followed by the raw sequence.
This converter reads each GenBank entry, extracts the accession or locus identifier along with the DEFINITION and ORGANISM, and assembles them into a FASTA header. It then reads the ORIGIN block, strips out the position numbers and spacing, concatenates the bases into a continuous string, and rewraps it into fixed-width lines. The important thing to understand is what is preserved and what is lost. The nucleotide sequence and a short description survive, but the feature annotations, references, taxonomy lineage, and other structured metadata are intentionally discarded — FASTA has nowhere to put them. If you need those annotations later, keep the original GenBank file, because the conversion is one-way.
Common Use Cases
- Preparing sequences downloaded from NCBI for a BLAST search
- Feeding sequences into multiple sequence alignment tools such as Clustal or MAFFT
- Building input files for phylogenetic analysis
- Supplying plain sequence to custom scripts and pipelines that expect FASTA
- Reducing large annotated records to compact, easily parsed sequence files
Frequently Asked Questions
What information is lost when converting GenBank to FASTA?
FASTA keeps only a header line and the sequence, so the feature table, literature references, taxonomy lineage, keywords, and most other structured annotation in the GenBank record are dropped. The nucleotide sequence itself and a short description are retained. Because FASTA cannot store the extra metadata, always keep the original GenBank file if you may need it later.
Can I convert several GenBank records at once?
Yes. If you paste a multi-record GenBank file, the tool splits it at each LOCUS line and produces one FASTA entry per record, so a single conversion can turn a whole batch of annotated sequences into a multi-FASTA file.
Is my sequence data uploaded to a server?
No. The conversion runs entirely in your browser using client-side JavaScript. Your GenBank data is never sent to a server, which makes the tool suitable for working with unpublished or sensitive sequences.
Why is the FASTA sequence wrapped into short lines?
By convention, FASTA sequences are wrapped to a fixed line width so files stay readable and compatible with older tools. The wrapping is purely cosmetic — the sequence is identical whether it appears on one long line or many shorter ones.
Can I convert FASTA back to GenBank with this tool?
No. Conversion only goes from GenBank to FASTA. Rebuilding a GenBank record would require feature annotations and metadata that FASTA does not contain, so those details cannot be recovered from a FASTA file alone.
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