NCBI introduces Datasets, a new resource that lets you easily gather data from across NCBI databases. Our first release allows you to find and download genomic sequence and annotation data for all eukaryotic organisms through our user-friendly web interface.
Our web interface also provides an interactive taxonomy tree that lets you browse for your favorite organism. We are currently testing the web interface in the NCBI labs environment. To try it out, enter a taxonomic name or assembly accession and click on the ‘Get Data’ button in the search results panel.
NCBI Labs is showcasing an experiment to improve the BLAST results page. The goal is to provide a more useful BLAST output that better meets your needs and integrates with your workflows. The new results incorporate feedback from surveys and interviews with BLAST users. We think you’ll find the new results are more compact, easier to navigate, and expose useful formatting and other features that you may not have known about.
The results page has organism, percent identity, and E value filters in plain view and easily accessible. The Descriptions and Graphic Summary are on separate tabs, and the popular taxonomy view is on a fourth tab rather than on a separate web page. These changes along with other enhancements make the display more concise and easier to navigate. The figure below shows the new output format.
Figure 1. The New BLAST Results with filters directly on the page and a more concise tabbed output that includes the taxonomy report. The Back to Traditional Results Page link re-loads the results in the standard format.
In late May, we introduced a new type of search experience in NCBI Labs that uses natural language queries to make common tasks easier. The experience at NCBI Labs – where we experiment with potential new features and tools – proved successful. We’re pleased to announce that we added this simplified search capability to NCBI’s global search page. Some natural language queries now work in the “All Databases” search from the NCBI home page!
In a recent post, we described a new way to search our databases in NCBI Labs. We have now added a suggestions dropdown to the search bar that should make life easier for many NCBI visitors.
The as-you-type suggestions are simple, natural language-like queries we described in the previous post. They’ll help you avoid typos and save time if you’re searching for organisms with long or hard-to-spell names.
These suggestions are meant to direct you to high value results. As we improve the search experience, you may notice changes to the suggestions. We welcome your feedback on ways to enhance this new feature.
Almost two years ago, we launched PubMed Journals, an NCBI Labs project. PubMed Journals helped people follow the latest biomedical literature by making it easier to find and follow journals, browse new articles, and included a Journal News Feed to track new arrivals news links, trending articles and important article updates.
PubMed Journals was a successful experiment. Since September 2016, nearly 20,000 people followed 10,453 distinct journals. Each customer followed 3 journals on average.
Though PubMed Journals will no longer exist as a separate entity, we hope to add its features into future NCBI products. We appreciate your feedback over the years that made PubMed Journals a productive test of new ideas.
NCBI Labs is NCBI’s product incubator for delivering new features and capabilities to NCBI end users.
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.
BLAST is a powerful search tool, but often a search is just the beginning of the journey. We put ourselves in the shoes of a researcher who has just sequenced a handful of samples from the latest viral outbreak and tried to understand what information would be most useful. We also reached out to researchers in the field and asked: a) what questions do they really want to answer? and b) how can NCBI best provide the answers? Based on insights from those questions and answers, we developed the new Virus Sequence Search Interface (Fig. 1). The Search Interface is an NCBI Labs project, which means it is an experimental project, and we may modify the resource based on your feedback and experiences.
About two years ago, NCBI launched PubMed Labs, a gathering place for discovering and experimenting with new features and content for NCBI’s family of websites. Over those years, we launched a few experiments that have helped us learn more about our customers and how we can serve them better.
Today we’re happy to announce that we’re expanding PubMed Labs to a broader set of experiments called NCBI Labs.
Why are we doing this?
To better convey the breadth of upcoming experiments on data, services, and websites that NCBI offers now and hopes to offer in the future. You can expect to see new features, content, and other experiments from NCBI Labs in the coming months.
This blog’s menu item and blog category “PubMed Labs” will now appear as “NCBI Labs”. Existing links will continue to work. We won’t be updating the old blog posts, for the most part, although some links on existing sites (e.g. on PubMed Journals) may be updated to use the new name.
ORFfinder is a graphical analysis tool for finding open reading frames (ORFs). We’ve been working on a few updates, and we’d like to find out what you think about them. Read on to find out what you can do with the new ORFfinder.