D10–D17 Nucleic Acids Research, 2021, Vol. 49, Database issue Published online 23 October 2020
doi: 10.1093/nar/gkaa892
Database resources of the National Center for
Biotechnology Information
Eric W. Sayers *
, Jeffrey Beck, Evan E. Bolton, Devon Bourexis, James R. Brister,
Kathi Canese, Donald C. Comeau, Kathryn Funk, Sunghwan Kim , William Klimke,
Aron Marchler-Bauer, Melissa Landrum, Stacy Lathrop, Zhiyong Lu , Thomas L. Madden,
Nuala O’Leary, Lon Phan, Sanjida H. Rangwala, Valerie A. Schneider, Yuri Skripchenko,
Jiyao Wang, Jian Ye, Barton W. Trawick, Kim D. Pruitt and Stephen T. Sherry
National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, Building
38A, 8600 Rockville Pike, Bethesda, MD 20894, USA
Received September 15, 2020; Revised September 25, 2020; Editorial Decision September 28, 2020; Accepted October 08, 2020
ABSTRACT
The National Center for Biotechnology Information
(NCBI) provides a large suite of online resources
for biological information and data, including the
GenBank®
nucleic acid sequence database and the
PubMed®
database of citations and abstracts published
in life science journals. The Entrez system
provides search and retrieval operations for most of
these data from 34 distinct databases. The E-utilities
serve as the programming interface for the Entrez
system. Custom implementations of the BLAST program
provide sequence-based searching of many
specialized datasets. New resources released in the
past year include a new PubMed interface and NCBI
datasets. Additional resources that were updated in
the past year include PMC, Bookshelf, Genome Data
Viewer, SRA, ClinVar, dbSNP, dbVar, Pathogen Detection,
BLAST, Primer-BLAST, IgBLAST, iCn3D and
PubChem. All of these resources can be accessed
through the NCBI home page at https://www.ncbi.
nlm.nih.gov.
INTRODUCTION
NCBI overview
The National Center for Biotechnology Information
(NCBI), a center within the National Library of Medicine
at the National Institutes of Health, was created in 1988
to develop information systems for molecular biology (1).
In this article we provide a brief overview of the NCBI
Entrez system of databases, followed by a summary of resources
that we either introduced or significantly updated
in the past year. We provide more complete discussions of
NCBI resources on the home pages of individual databases,
on the NCBI Learn page (https://www.ncbi.nlm.nih.gov/
learn/) and in the NCBI Handbook (https://www.ncbi.nlm.
nih.gov/books/NBK143764/).
The entrez system
Entrez (2) is an integrated database retrieval system that
provides access to a diverse set of 34 databases that together
contain 3.0 billion records (Table 1 and Figure 1). Links to
the web portal for each of these databases are provided on
the Entrez global search page (https://www.ncbi.nlm.nih.
gov/search/). Entrez supports text searching using simple
Boolean queries, downloading of data in various formats
and linking records between databases based on asserted relationships.
The records retrieved in Entrez can be displayed
in many formats and downloaded singly or in batches. An
Application Programming Interface for Entrez functions
(the E-utilities) is available, and detailed documentation is
provided at https://eutils.ncbi.nlm.nih.gov/.
Data sources and collaborations
NCBI receives data from three sources: direct submissions
from researchers, national and international collaborations
or agreements with data providers and research consortia,
and internal curation efforts. For example, NCBI manages
the GenBank database (3) and participates with the EMBLEBI
European Nucleotide Archive (ENA) (4) and the DNA
Data Bank of Japan (DDBJ) (5) as a partner in the International
Nucleotide Sequence Database Collaboration
(INSDC) (6). Details about direct submission processes are
available from the NCBI Submit page (www.ncbi.nlm.nih.
gov/home/submit.shtml) and from the resource home pages
(e.g. the GenBank page, www.ncbi.nlm.nih.gov/genbank/).
More information about the various collaborations, agreements,
and curation efforts are also available through the
home pages of the individual resources.
*To whom correspondence should be addressed. Tel: +1 301 496 2475, Fax: +1 301 480 9241; Email: sayers@ncbi.nlm.nih.gov
Published by Oxford University Press on behalf of Nucleic Acids Research 2020.
This work is written by (a) US Government employee(s) and is in the public domain in the US.
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Nucleic Acids Research, 2021, Vol. 49, Database issue D11
Table 1. The Entrez Databases (as of 9 September 2020)
Database Records Description
Literature
PubMed 31 471 600 scientific and medical abstracts/citations
PubMed Central 6 447 271 full-text journal articles
NLM catalog 1 619 856 index of NLM collections
Books 825 385 books and reports
MeSH 300 500 ontology used for PubMed indexing
Genomes
Nucleotide 429 731 711 DNA and RNA sequences
BioSample 14 628 076 descriptions of biological source materials
SRA 11 807 161 high-throughput DNA and RNA sequence read archive
Taxonomy 2 401 136 taxonomic classification and nomenclature catalog
Assembly 837 406 genome assembly information
BioProject 458 893 biological projects providing data to NCBI
Genome 55 580 genome sequencing projects by organism
BioCollections 8 138 museum, herbaria and other biorepository collections
Genes
GEO Profiles 128 414 055 gene expression and molecular abundance profiles
Gene 28 377 759 collected information about gene loci
GEO datasets 4 002 373 functional genomics studies
PopSet 350 627 sequence sets from phylogenetic and population studies
HomoloGene 141 268 homologous gene sets for selected organisms
Genetics
SNP 720 643 623 short genetic variations
dbVar 6 030 887 genome structural variation studies
ClinVar 845 008 human variations of clinical significance
MedGen 335 277 medical genetics literature and links
GTR 76 814 genetic testing registry
dbGaP 1 397 genotype/phenotype interaction studies
Proteins
Protein 874 272 642 protein sequences
Identical protein groups 329 946 078 protein sequences grouped by identity
Protein clusters 1 137 329 sequence similarity-based protein clusters
Structure 167 650 experimentally-determined biomolecular structures
Sparcle 149 462 conserved domain architectures
Conserved domains 59 951 conserved protein domains
Chemicals
PubChem substance 285 048 146 deposited substance and chemical information
PubChem compound 111 325 418 chemical information with structures, information and links
PubChem BioAssay 1 229 071 bioactivity screening studies
BioSystems 983 968 molecular pathways with links to genes, proteins and chemicals
RECENT DEVELOPMENTS
Literature updates
PubMed. After previewing an updated version of
PubMed in 2019, we activated this updated version as
the default system in May 2020. Among the numerous
enhancements is a responsive layout that offers better
support for accessing PubMed content on increasingly
popular small-screen devices such as mobile phones and
tablets. The interface is compatible with any screen size and
provides a fresh, consistent look and feel throughout the
application, no matter how one accesses it. Search results
can now be sorted using ‘Best Match’ ordering that employs
a machine learning algorithm to help users find relevant
citations quickly (7). Search results also include ‘snippets’,
highlighted text fragments from the article abstract that
are selected based on their relatedness to the query. These
snippets give users additional information to help them
decide if an article is useful. Additional improvements to
the interface make it easier to discover related content such
as similar articles, references and citations.
Since 2012 PubMed has allowed users to search for a distinct
author, and not merely for an author name, through
an automatic author name disambiguation algorithm (8).
We recently enhanced this algorithm by leveraging the significant
growth of ORCID use in PubMed articles. Users
can search PubMed directly with ORCIDs using the following
syntax: 0000-0001-6166-3199[auid]. Additionally, to
further strengthen how PubMed handles synonyms, we developed
and implemented an updated algorithm to obtain
word synonym pairs that improve PubMed indexing and retrieval
(9).
The updated version of PubMed takes advantage of several
new technologies to improve the user experience. The
underlying document data indexed in the updated version is
a merger of content from PubMed, Bookshelf and PubMed
Central (PMC). This combined dataset allows us to display
relevant information not previously available in a PubMed
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D12 Nucleic Acids Research, 2021, Vol. 49, Database issue
90.00%
80.00%
70.00%
60.00%
50.00%
40.00%
30.00%
20.00%
10.00%
0.00%
Assem
blyClinVar
IdenƟcalProtein
Groups
SRA
GTR
BioSam
ple
BioProject
GEO
DataSets
Genom
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PubChem
Substance
PubChem
Com
pound
PubChem
BioAssayProtein
PubM
ed
CentralGeneBooks
StructureM
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Taxonom
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NucleoƟde
SNP
Conserved
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PubM
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M
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NLM
Catalog
BioCollecƟons
Protein
Clusters
GEO
Profiles
Hom
oloGene
BioSystem
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AnnualGrowth
Figure 1. Annual growth rates of the number of records in each Entrez database as of 9 September 2020.
record, such as reference citations from PMC. While legacy
PubMed limited the number of variants for a wildcard
(‘*’) search, PubMed is now capable of unlimited wildcard
searches thanks to Solr (https://lucene.apache.org/solr/), the
open-source enterprise search system that PubMed now
uses for document indexing. Users will find that PubMed
now has greater scalability and reliability, provided not only
by Solr, but also by the MongoDB storage solution and the
modern cloud architecture that together ensure both redundancy
between data centers and also trustworthy backup
environments. When visiting PubMed, users will enjoy a
modern web experience using the latest web technologies
and standards, all provided by the Django web framework.
PubMed Central (PMC). PMC continued to expand access
to biomedical and life science literature over the past
year, with the corpus now including more than 6 million
journal articles and author manuscripts. Reflecting the
NLM’s ongoing commitment to public access to research
results supported by the NIH and other funding partners,
we released a new NIH Manuscript Submission (NIHMS)
system in January 2020. The new NIHMS system streamlines
the author manuscript submission process to PMC
and offers more transparent options to aid authors and
investigators in avoiding processing delays and ensuring
timely compliance with NIH policy. In the first 6 months
after release, we received nearly 40 000 successful submissions
(https://www.nihms.nih.gov/about/statistics/).
PMC launched the Public Health Emergency COVID-19
Initiative (https://www.ncbi.nlm.nih.gov/pmc/about/covid-
19/) in March 2020, which helped enable the creation of
the COVID-19 Open Research Dataset (CORD-19) hosted
by the Allen Institute. This initiative resulted from a call
made by the national science and technology advisors of
a dozen countries, including the US, to support ongoing
public health emergency response efforts. Specifically, this
call asked publishers and societies to agree voluntarily to
make their publications and supporting data related to
COVID-19 and the novel coronavirus immediately accessible
in PMC and other appropriate public repositories. As
of August, this initiative included more than 50 publishers
and has added or updated the licenses on 80 000 articles in
PMC to support secondary re-use and analysis.
On 9 June 2020, NLM launched a pilot project to test the
viability of allowing users to obtain from PMC preprints resulting
from NIH-funded research (https://www.ncbi.nlm.
nih.gov/pmc/about/nihpreprints/). The primary goal of this
NIH Preprint Pilot is to explore approaches to increase
the discoverability of early NIH research results. Following
standard NLM practice, citations for these preprint
records are available in PubMed to increase the discoverability
of this content. To ensure transparency, large banners
clearly identify these preprint records in PMC and
PubMed. The banners explain that the papers have not been
peer reviewed, and link to information about the pilot for
additional context. The pilot will run for a minimum of 12
months and will focus on preprints that relate to the current
COVID-19 pandemic. Lessons we learn during that time
will inform future NLM efforts involving preprints.
Bookshelf. The NCBI Bookshelf provides free online access
to over 8500 books and documents in life science and
healthcare from over 150 content providers. In the past year,
we migrated the content management of two large full-text
toxicology databases into its archive. The first, LactMed, is
an NLM database of over 1500 peer-reviewed summaries
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Nucleic Acids Research, 2021, Vol. 49, Database issue D13
containing information on drugs and other chemicals to
which breastfeeding mothers may be exposed. It also includes
information on the levels of such substances in breast
milk and infant blood, and the possible adverse effects in
the nursing infant. The second, LiverTox, is an NIDDK
database of over 1100 peer-reviewed documents containing
information on the diagnosis, cause, frequency, clinical
patterns and management of liver injury attributable
to both prescription and nonprescription medications and
also selected herbal and dietary supplements. Migrating
these full-text databases into the Bookshelf increases their
discoverability in two ways: the citations for each full-text
LactMed and LiverTox summary record are now available
in PubMed, where they link to the full-text in Bookshelf;
and the toxicological data for these records are seamlessly
integrated in PubChem with the scientific evidence summarized
and cited in the full-text documents in Bookshelf.
Users can still search within LactMed or LiverTox, and the
full-text, machine-readable records for both are available
through the NLM LitArch Open Access subset for data
mining and reuse.
Genome updates
NCBI Datasets. We have continued to develop improvements
to sequence search through the introduction of
Datasets, a new resource that enables users to easily gather
content from across NCBI databases (https://www.ncbi.
nlm.nih.gov/datasets/). Developed with the FAIR (findability,
accessibility, interoperability and reusability) principles
of data management in mind, Datasets allows users to
create custom datasets through web, RESTful API, and
command-line interfaces, and download them in structured
file packages. As of this writing, Datasets supports queries
for genomes and genes across a wide range of taxonomies,
including quick access to SARS-CoV-2 genomes and proteins.
Users searching for genomic data can assemble a
package consisting of genome, transcript and protein sequences
as well as annotations. The package will also include
a data report with rich metadata. The Datasets web
interface (Figure 2) allows users to browse genomes on a
taxonomic tree and choose any set of complete eukaryotic
genomes in the NCBI Assembly database. The API and
command-line interfaces provide access to prokaryotic and
viral genomes in addition to eukaryotic genomes, and support
searches with taxonomic identifiers or assembly accessions.
For gene searches, Datasets allows users to construct
data tables based on either an NCBI Gene ID or a combination
of organism and gene symbol. On the web interface,
users can continue editing the set of genes on the table and
then select a set of desired data columns before downloading
the data. The API and command-line interfaces provide
similar tables programmatically. A Python library and corresponding
Jupyter notebooks allow users to explore and
learn the datasets API, and these are available on GitHub
(https://github.com/ncbi/datasets).
Graphical sequence viewers. NCBI’s graphical sequence
viewer tools visualize sequences, annotations and experimental
data alignments archived in NCBI databases. These
viewers include the NCBI Sequence Viewer (SV) and the
Multiple Sequence Alignment Viewer (MSAV). SV is available
as a standalone application (https://www.ncbi.nlm.nih.
gov/projects/sviewer/) and also appears as a fully-functional
embed on many NCBI pages, including Gene and SNP
records and the NCBI Variation Viewer. SV is also the
graphical viewer for Nucleotide and Protein records and
the BLAST (10) and Primer-BLAST (11) results pages.
MSAV (https://www.ncbi.nlm.nih.gov/projects/msaviewer/)
displays multiple sequence alignments created by NCBI
BLAST, COBALT and NCBI Virus pages, and also displays
custom alignments from researchers.
In the last year, we have further enhanced the sequence
and data download capabilities within SV (https://www.
ncbi.nlm.nih.gov/tools/sviewer/). Users can now download
gene, feature and NCBI SNP annotation data from the
graphical view tool in multiple common formats that include
GFF3, VCF and BED. Users can also copy short
strings of sequence data directly to the clipboard and can
also download larger ranges in FASTA or GenBank flat file
format. Improved tooltips now report positional information
that changes dynamically depending on the position
of the cursor. For gene features, including transcript and
proteins, the tooltip provides the transcript, CDS, and/or
protein position and exon or intron number. For BAM,
SRA or BLAST alignments, the tooltip information also includes
the ability to view any unaligned data, including insertions
and 5 and 3 tails. Recent enhancements to NCBI’s
MSAV (https://www.ncbi.nlm.nih.gov/tools/msaviewer/) allow
users to re-sort rows to find sequences of interest and
then customize their display further by ‘hiding’ undesired
sequences from view (such as partial or duplicate alignments)
or in their SVG/PDF image output.
Genome data viewer. NCBI’s flagship genome browser,
Genome Data Viewer (GDV) (https://www.ncbi.nlm.nih.
gov/genome/gdv/), integrates the SV graphical display with
a robust search/retrieval/analysis console. Users can view
their own data next to NCBI tracks as references. In our
endeavor to better support our users’ analyses and research
needs, we released numerous enhancements in the past year.
Of particular note is a dynamic sidebar that users can show
or hide. Hiding the sidebar allows the graphical display to
stretch for a wider view. Additional enhancements now allow
navigation by assemblies, chromosomes and components
directly from within the browser.
Users interested in non-human variation data can now
add SNP data from the European Variation Archive as
tracks directly to the view using the tracks configuration
menu in SV. Researchers can also add their own or thirdparty
data by streaming data hosted on external URLs.
GDV also supports connectivity to UCSC-style track hubs
directly from the EBI Track Hub Registry. GDV supports
visualization of most common bioinformatics formats including
GFF3, bigWig, multiWig, bigBED and indexed
BAM and VCF files. Helpful tutorials to get started are
available on the NCBI YouTube channel in the ‘NCBI
Genome Data Viewer’ playlist. Additional documentation
is available at https://www.ncbi.nlm.nih.gov/genome/gdv/
browser/help/.
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Figure 2. Landing page for the new NCBI Datasets product (https://www.ncbi.nlm.nih.gov/datasets/) that provides packaged downloads of genomic
datasets using either a web interface, an API, or a UNIX/LINUX command-line tool.
Sequence Read Archive. NCBI maintains the NIH Sequence
Read Archive (SRA), an archival database designed
to support storage, retrieval and analysis of nextgeneration
nucleotide sequence data. This archive now includes
8.8 Petabytes of publicly available data and another
4.6 Petabytes of controlled-access dbGaP data. While the
archive holds tremendous promise for biomedical research,
the sheer size of this dataset makes it difficult to store, retrieve
and analyze. NCBI remains committed to continuing
to expand SRA and improving access to the archive based
on FAIR data principles.
As part of the NIH Science and Technology Research
Infrastructure for Discovery, Experimentation and Sustainability
Initiative (https://datascience.nih.gov/strides/),
NCBI is now maintaining the entire SRA on two commercial
cloud platforms, Amazon Web Services (AWS) and
Google Cloud Platform (GCP). The cloud environment
offers many advantages for the transfer and analysis of
data (12), and the availability of SRA on cloud platforms
should facilitate large-scale computational operations and
collaborations. This idea has been supported by early pilot
experiments in which thousands of metagenomic samples
were analyzed for organismal content using cloud-adapted
workflows and software (13). An additional example are
COVID-focused datasets (including source and normalized
SRA file formats) recently added to the AWS Public Dataset
Program. These datasets provide researchers easy, no-cost
access to more than 13 000 SRA runs that include Coronaviridae
content identified by a kmer-based approach using
the SRA Taxonomy Analysis Tool.
We have made several additional updates that allow more
effective use of cloud-hosted SRA data. By providing SRA
run metadata and BioSample data on GCP BigQuery and
AWS Athena, we give researchers more ways to identify sequence
sets of interest. In addition to maintaining originally
submitted source and SRA formatted data in the cloud, we
are introducing normalized data formats that bin base quality
scores to binary read assessments or align reads to references.
These reduce file size and can expedite certain computations.
We have also updated the SRA data location service
and toolkit (https://github.com/ncbi/sra-tools/wiki/02.
-Installing-SRA-Toolkit) to retrieve data from cloud locations
in the desired data format.
Pathogens. The NCBI Pathogen Detection Project (https:
//www.ncbi.nlm.nih.gov/pathogens/) helps public health
scientists investigate foodborne disease outbreaks by integrating
pathogen genomic sequences obtained from cultured
bacterial isolates and quickly clustering and identifying
related sequences (14). As of August 2020, over 600
000 pathogen isolates covering 31 bacterial taxa and one
emerging fungal pathogen, Candida auris, are actively be-
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ing analyzed. We make these analysis results available in the
Isolates Browser on a daily basis (https://www.ncbi.nlm.nih.
gov/pathogens/isolates). As part of our effort to improve
the compliance of the pipeline results (15) with FAIR principles,
we annotate the generated assemblies using PGAP
(16), submit them to GenBank and incorporate them into
the NCBI Assembly resource. These assemblies link back
to the Isolates Browser and also to the SNP Tree Viewer if
that particular isolate is a member of a clonally related cluster.
The Isolates Browser allows users to subset isolates and
then download the assembled sequence and/or annotation
of the submitted assemblies.
Antimicrobial resistance (AMR) resources. The Pathogen
Detection team has continued to improve and release
updated resources for antimicrobial resistance (AMR)
(https://www.ncbi.nlm.nih.gov/pathogens/antimicrobialresistance/).
The Reference Gene Catalog (https:
//www.ncbi.nlm.nih.gov/pathogens/isolates#/refgene/)
now provides a searchable and browsable interface for two
sets of genes: a ‘core’ AMR reference set of acquired genes
and proteins as well as point mutations conferring AMR,
and a ‘plus’ set of genes related to stress responses (acid,
metal, heat and biocide) and virulence. The 16 July 2020 release
included 6428 total proteins (5588 AMR proteins, 210
stress response proteins and 630 virulence proteins) as well
as 682 point mutations. We also released an updated version
of the AMRFinder software (17) called AMRFinderPlus
that uses the reference set above (https://www.ncbi.nlm.nih.
gov/pathogens/antimicrobial-resistance/AMRFinder/). All
isolates in the Pathogen Detection Isolates Browser other
than C. auris are analyzed with AMRFinderPlus, and the
three categories of genes (AMR, stress and virulence) are
available in the Isolates Browser. Currently over 590 000
isolates have at least one identified AMR gene, over 510
000 have at least one identified stress response gene and
over 210 000 have at least one identified virulence gene.
For the subset of isolates from the Isolates Browser
that are both deposited in GenBank and that have genes
identified by AMRFinderPlus, a new tabular viewer called
the Microbial Browser for Genetic and Genomic Elements
is available (MicroBIGG-E, https://www.ncbi.nlm.
nih.gov/pathogens/isolates#/microbigge/). Every row in the
MicroBIGG-E viewer displays a gene or point mutation
that has been identified. This new interface provides easy
access to the gene and contig sequences to facilitate further
analyses. The Isolate Browser and MicroBIGG-E allow
cross-browser selection, so that selections of isolates in
the Isolate Browser enable selections of genes they encode
in MicroBIGG-E and vice versa.
Genetics updates
ClinVar. ClinVar is an archive of submitted reports of relationships
among human variations and phenotypes with
supporting evidence. In December 2019, ClinVar reached
the milestone of 1 million submitted records, representing
more than half a million variants. To support ClinVar’s continued
growth, we have improved the submission processing
pipeline so that submitted data can be published faster.
From October 2019 to August 2020, we added validation
to the ClinVar Submission Portal so that all of the required
fields in a file submission are validated before the file is submitted
to ClinVar. As of August 2020, submitters also have
the option to stop a submission and correct errors immediately,
or to submit all records that pass validation and receive
a report of any failures to correct later.
In January 2020, we added a new feature to ClinVar that
allows a user to ‘follow’ a particular variant and be notified
if the overall clinical interpretation in ClinVar changes, for
example from a pathogenic category to a non-pathogenic
one. This feature makes it easier for a laboratory to become
aware of variants that may need to be re-evaluated, and for
clinicians to know when they should contact their clinical
testing laboratory and/or patient with new information.
dbSNP. The Database of Single Nucleotide Polymorphisms
(dbSNP) is a repository of human genomic variations
and frequency data that includes both common and
rare single-nucleotide variations and other small-scale variations.
In 2020 dbSNP released the new NCBI Allele Frequency
Aggregator (ALFA) dataset (https://www.ncbi.nlm.
nih.gov/snp/docs/gsr/alfa/). We calculated the ALFA frequency
data from 98 500 dbGaP subjects for whom genotypes
were available. Aggregated from 551 billion genotypes,
the results include allele counts and frequencies
for 443 million known variations and 4 million novel
ones. Future ALFA releases will include additional dbGaP
studies, and we expect the dataset to expand to
over a billion variants from millions of subjects. The
ALFA data are available as part of the dbSNP regular
release (https://ftp.ncbi.nih.gov/snp/latest release/) and
also as a separate download (https://ftp.ncbi.nih.gov/snp/
population frequency/latest release/). The ALFA data are
also accessible through an API (https://www.ncbi.nlm.nih.
gov/snp/docs/gsr/alfa/#api-queries).
dbVar. In the past year, dbVar added 20 new human structural
variation studies, bringing the total in the database to
190 studies containing 6 million regions and 36 million variants.
Some notable studies are the Decipher dataset (https:
//www.ncbi.nlm.nih.gov/dbvar/studies/nstd183), gnomAD
(https://www.ncbi.nlm.nih.gov/dbvar/studies/nstd166/) and
the NCBI Curated Common Structural Variants dataset
(https://www.ncbi.nlm.nih.gov/dbvar/studies/nstd186) that
includes frequency data. dbVar continues to make it easier
to find and use structural variation data by making selected
datasets available on TrackHub for viewing in the
NCBI GDV and other genome browsers, such as the UCSC
browser. Tracks are available for the structural variants imported
from ClinVar (https://www.ncbi.nlm.nih.gov/dbvar/
content/clinvar summary/#homepage) and for the NCBI
Curated Common Structural Variants (nstd186).
BLAST updates
BLAST in the cloud. In the past year we have made
some important changes to our BLAST databases.
We released a new version of BLAST databases (v5)
that are taxonomically aware, allowing users to limit a
stand-alone BLAST+ search (18) by taxonomy using
information stored in the database. To take advantage
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of this feature, users will need a recent version of the
BLAST+ package (2.9.0 release or later). The older
BLAST database version (v4) has been deprecated.
The new BLAST databases are available on the NCBI
FTP site as well as on GCP and AWS cloud providers,
and all three sites now offer the same 23 databases.
These databases range from a Betacoronavirus collection
(https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE TYPE=
BlastSearch&BLAST SPEC=Betacoronavirus) to RefSeq
representative genomes for eukaryotes, prokaryotes
and viruses. Also included are the default NCBI
nucleotide collection (nt), the non-redundant protein
(nr) database, and genome assemblies for human
and mouse. On AWS and GCP, users can access these
databases with the BLAST+ Docker package described
at https://github.com/ncbi/blast plus docs. Additionally,
four databases based on the NCBI Targeted Loci Project
(including collections of 18S, 28S and prokaryote 16S
ribosomal RNA genes along with a database of fungal
internal transcribed spacers) have been added to both the
BLAST webpage and are also available as stand-alone
databases on the NCBI FTP site and on GCP and AWS.
Primer-BLAST. Primer-BLAST (11) now allows users to
design primers that are common for a group of highly similar
sequences. This makes it easier for researchers to perform
tasks such as amplifying multiple transcript variants
for a single gene or detecting a group of highly related bacteria
strains. Another new feature allows users to set the maximal
nucleotide match at the 3 end of exon-exon junctions
of transcripts to address non-specific polymerase chain reaction
amplification.
IgBLAST. We have added several new features to IgBLAST
(19). IgBLAST now supports annotations of the
FWR4 region so that the entire V region can be annotated.
Another new feature is that IgBLAST indicates if a
sequence has a complete V(D)J region so that users can
keep track of sequences with a full V region. Additional
new functions include allowing users to extend J gene alignments
at the 3 end and to analyze sequences from an organism
of their choice.
Protein updates
NCBI released an updated version (2.19.0) of iCn3D (20),
a three-dimensional (3D) molecular structure viewer that
runs directly in web browsers. Interactive iCn3D views are
embedded in structure summary pages of NCBI’s Molecular
Modeling Database (MMDB), and iCn3D visualizes the
results of 3D structure comparisons computed by VAST+
as well as pairwise sequence-to-structure alignments computed
by protein BLAST. iCn3D simultaneously displays
3D structures, 2D interaction schematics, alignments and
protein/nucleotide sequences, as well as sequence annotations
such as functional sites and conserved domain footprints.
Sequence variations can be displayed for some human
protein structures, and recently we have made sequence
variation data accessible for selected structures of
SARS-CoV-2 proteins. Other recently added features include
extended visualization of 2D interaction networks
between proteins and ligands or other proteins, visualization
of electrostatic potentials as computed by Delphi
(21) and visualization of membrane bilayer location relative
to membrane protein structures as provided by OPM
(22). Finally, a Jupyter notebook widget version of iCn3D
(called icn3dpy) enables users to view 3D structures in a
Jupyter environment. iCn3D is available at https://github.
com/ncbi/icn3d, and novel features are demonstrated on
the gallery page at https://www.ncbi.nlm.nih.gov/Structure/
icn3d/icn3d.html#gallery.
Chemical updates
PubChem (23–25) (pubchem.ncbi.nlm.nih.gov) is a public
chemical data repository at NCBI. Over the past year,
PubChem expanded the scope of its information content
by integrating data from more than 50 new data
sources. Notably, the World Intellectual Property Organization
(WIPO) provided PubChem with more than 16 million
chemical structures searchable in its patent database called
PATENTSCOPE (https://go.usa.gov/xdhfK). In addition,
SpringerMaterials provided links to hundreds of chemical
and physical properties for more than 32 000 compounds,
helping users to quickly locate articles for the property in
question (https://go.usa.gov/xvqfq). Another new source of
data came from ToxNet, a collection of NLM databases
that provided a wide range of toxicological information.
These databases were retired last year and their content
was integrated into PubChem (https://go.usa.gov/xfwyU).
They include the Genetic Toxicology Data Bank (GeneTox),
the Chemical Carcinogenesis Research Information
System (CCRIS), the Hazardous Substances Data Bank
(HSDB), ChemIDplus, LactMed and LiverTox. Finally, in
response to the COVID-19 pandemic, PubChem created a
special data collection containing data related to COVID-
19 and SARS-CoV-2 (https://go.usa.gov/xfwmG). We gathered
the data in this collection from authoritative and curated
sources, and a link to the collection appears on the
PubChem home page.
FOR FURTHER INFORMATION
The resources described here include documentation, other
explanatory materials and references to collaborators and
data sources on their respective web sites. An alphabetical
list of NCBI resources is available from a link above the
category list on the left side of the NCBI home page. The
NCBI Help Manual and the NCBI Handbook (www.ncbi.
nlm.nih.gov/books/NBK143764/), both available as links in
the common page footer, describe the principal NCBI resources
in detail. The NCBI Learn page (www.ncbi.nlm.
nih.gov/learn/) provides links to documentation, tutorials,
webinars, courses and upcoming conference exhibits. A variety
of video tutorials are available on the NCBI YouTube
channel that can be accessed through links in the standard
NCBI page footer. A user-support staff is available to
answer questions at info@ncbi.nlm.nih.gov, and users can
view support articles at https://support.nlm.nih.gov. Updates
on NCBI resources and database enhancements are
described on the NCBI Insights blog (https://ncbiinsights.
ncbi.nlm.nih.gov/), NCBI social media sites (FaceBook,
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Nucleic Acids Research, 2021, Vol. 49, Database issue D17
Twitter and LinkedIn) and the several mailing lists and RSS
feeds that provide updates on services and databases. Links
to these resources are in the NCBI page footer and on NCBI
Insights.
ACKNOWLEDGEMENTS
The authors would like to thank all of the NCBI staff who
through their dedicated efforts continue to allow NCBI to
provide our full collection of services to the community.
FUNDING
Funding for open access charge: National Institutes of
Health. Funding to pay the Open Access publication
charges for this article was provided by the Intramural Research
Program of the National Library of Medicine, National
Institutes of Health.
Conflict of interest statement. None declared.
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