We know it’s not always easy to find the sequence data you’re after at NCBI. Maybe it’s because you’re no expert at constructing queries, and you end up with no results or too many results. Or maybe you’re an Entrez wizard, but creating a query full of Booleans and filters seems like overkill when you could just write a short natural language query, like you’re used to doing in Google.  The next time you search for a gene, transcript or genome assembly for a given organism, try the new search experience we’re piloting in NCBI Labs.

In NCBI Labs, you can now search for sequences using natural language and get the best results.

The improved search experience now available in NCBI Labs addresses 3 types of queries that commonly fail in searches at NCBI: organism-gene (e.g. human BRCA1), organism-transcript (e.g. Mouse p53 transcripts) and organism-assembly (e.g. dog reference genome). For each of these query types in NCBI Labs, we now return NCBI’s highest quality sequence sets or reference and representative assemblies in an easy-to-view panel.

Example queries are shown below to get you started.

Genes (query by: species level organism name + gene symbol or alias)

• human BRCA1
• Zea maize TIP4-3
• psmb5 Danio rerio
• human DACOR1
• Caenorhabditis elegans daf-16

Transcripts (query by: species level organism name + gene symbol or alias + mRNA/transcript/CDS)

• Homo sapiens CELF4 mRNA 
• Homo sapiens CD6 transcript
• human a2mp1 mrna
• Bos Taurus MCM9 transcript
• mouse p53 cDNA

Assemblies (query by: species level organism name + genome term OR assembly name)

• human assembly
• crassostrea gigas genome
• hg38
• mm10

We’re also measuring interest in accessing a single ‘selected’ representative transcript for a gene versus accessing all transcripts for a gene. The RefSeq Select label identifies a preliminary representative transcript. RefSeq Select is only provided for human genes now; the data set is not finalized. NCBI (RefSeq) and EMBL-EBI (Ensembl) are working together to provide a common minimal set of identical transcripts per human gene. RefSeq will extend the selection logic to other organisms in the future. We look forward to your feedback on these experiments.

We want to know what you think!

What’s working well? What’s not? What’s missing? Click the “Feedback” button at the bottom right of the NCBI Labs page to let us know.

Stay tuned to this blog for future announcements about the roll-out of the new search functionality on the main NCBI sites, as well the introduction of additional search improvements in NCBI Labs.

• NCBI Labs
• What's New