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The European Bioinformatics Institute's data resources


Abstract and Figures

The wide uptake of next-generation sequencing and other ultra-high throughput technologies by life scientists with a diverse range of interests, spanning fundamental biological research, medicine, agriculture and environmental science, has led to unprecedented growth in the amount of data generated. It has also put the need for unrestricted access to biological data at the centre of biology. The European Bioinformatics Institute (EMBL-EBI) is unique in Europe and is one of only two organisations worldwide providing access to a comprehensive, integrated set of these collections. Here, we describe how the EMBL-EBI’s biomolecular databases are evolving to cope with increasing levels of submission, a growing and diversifying user base, and the demand for new types of data. All of the resources described here can be accessed from the EMBL-EBI website:
Content may be subject to copyright.
The European Bioinformatics Institute’s data
Catherine Brooksbank*, Graham Cameron and Janet Thornton
EMBL—European Bioinformatics Institute, Wellcome Trust Genome Campus, Hinxton, Cambridge CB10 1SD, UK
Received October 14, 2009; Accepted October 15, 2009
The wide uptake of next-generation sequencing
and other ultra-high throughput technologies
by life scientists with a diverse range of interests,
spanning fundamental biological research,
medicine, agriculture and environmental science,
has led to unprecedented growth in the amount of
data generated. It has also put the need for
unrestricted access to biological data at the centre
of biology. The European Bioinformatics Institute
(EMBL-EBI) is unique in Europe and is one of only
two organisations worldwide providing access
to a comprehensive, integrated set of these
collections. Here, we describe how the EMBL-
EBI’s biomolecular databases are evolving to cope
with increasing levels of submission, a growing and
diversifying user base, and the demand for new
types of data. All of the resources described here
can be accessed from the EMBL-EBI website:
New DNA sequencing methods are revolutionising
biology, with impacts throughout the pure and applied
life-sciences. In the last five years there have been spectac-
ular improvements in the speed, capacity and affordability
of genome sequencing (1). This has made it feasible to
perform large-scale studies of broad application to
medicine, agriculture and environmental science. These
will enable humankind to gain a deeper understanding
of human variability (, unravel
the links between genetic variation and disease (www., identify and select for high yield and
disease resistance in agricultural crops (2), and catalogue
biodiversity ( with the aim
of improving species conservation.
The European Bioinformatics Institute, part of the
European Molecular Biology Laboratory (EMBL-EBI),
has a mandate to provide biomolecular data resources of
universal relevance to biological and medical research.
Although its focus is European, its impact is global and
it is the European node in several worldwide collaborative
initiatives to collect, organise and disseminate data for the
life-sciences. Demand for access to these data is high and
continues to grow, averaging 3.5 million web requests on
the EMBL-EBI website each day. Approximately 300 000
unique users visit the EMBL-EBI website every month,
and close to a million jobs per month are performed
using the EMBL-EBI’s web-services.
The roots of the EMBL-EBI’s data collection lie in
the world’s first public database of DNA sequences,
developed at the European Molecular Biology
Laboratory in Heidelberg in the early 1980s. To this
day, the European Nucleotide Archive (ENA) (3) is a
central pillar of the EMBL-EBI, not only because DNA
is the code of life and a reference point for objects in other
databases, but also because it set precedents that have
become established principles for the management of bio-
logical research data. These include: providing open and
unrestricted access to the data; setting up data sharing
agreements among globally important data collections;
and working with journal publishers to ensure that data
forming the basis of scientific publications are submitted
to appropriate databases and become part of the public
record of science (Box 1).
The EMBL-EBI was established as an Outstation of
EMBL in during the 1990s. It was already collaborating
with the Swiss Institute of Bioinformatics to develop the
Swiss-Prot and TrEMBL Protein sequence databases, and
soon began collaborating with the Protein Data Bank on
protein structure data. Up until this point, life-science
research still focused on studying one gene or one
protein at a time, but the completion of the first full
genome sequences marked an important turning point:
whole genome analysis became possible; high-throughput
technologies for studying transcripts, proteins, small
molecules and structures on a genome-wide scale began
to be widely adopted, and the era of reductionism began
to make way for systems biology. Our desire to keep pace
with researchers’ demand for open access to new data
types, coupled with the need to standardise data in differ-
ent databases, has driven a significant expansion of
the EMBL-EBI’s core set of databases (Figure 1).
*To whom correspondence should be addressed. Tel: +44 1223 492525; Fax: +44 1223 494468; Email:
Published online 24 December 2009 Nucleic Acids Research, 2010, Vol. 38, Database issue D17–D25
ßThe Author(s) 2009. Published by Oxford University Press.
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (
by-nc/2.5/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
These ‘core’ databases are those that aim to provide
complete collections of generic value to life-science. They
fall roughly into two categories: those describing the
molecular components of biological systems (nucleotide
sequences, protein sequences, macromolecular structures
and small molecules, for example) and those describing
their ‘behaviours’ or the outcomes of those behaviours
(transcription, translation and interaction, for example).
In addition to the core databases, the EMBL-EBI also
hosts a large number of specialist data resources. Two
examples are reviewed in this database issue and illustrate
the variety of applications and communities that the
EMBL-EBI’s databases support: the European Mutant
Mouse Archive (4), a partner in the International Mouse
Phenotyping Consortium, provides information on mouse
mutant strains, enabling life-science researchers to link
phenotypic information to mutations, and to source
mouse lines for their research. The non-redundant
patent-sequence database collection (5) was created
through a long-standing collaboration between the
European Patent Office and the EMBL-EBI. It provides
open access to sequences associated with patent
applications—of broad utility not only to intellectual
property specialists searching for prior art, but also to
the research community as a whole, because sequences
published in patent applications may not be published
elsewhere, and the patent applications may contain
unique scientific information.
Here we provide a bird’s eye view of the EMBL-EBI’s
core biomolecular database collection, describing the
rationale for recent launches and major developments,
and providing a starting point for users. Several reviews
of individual EMBL-EBI data resources are provided in
this issue and are cross-referenced here.
Figure 1. The EMBL-EBI’s core data resources, colour coded according to whether they focus on molecular entities or molecular behaviours.
Box 1. The EMBL-EBI’s principles of service provi-
Accessibility—We are the custodians (not the
owners) of biological data provided by the commu-
nity, and progress in biological research depends on
completely open access to these data. All our data
and tools are therefore freely available to the
research community, without restriction.
Compatibility—The EMBL-EBI has possibly done
more than any other organisation in the world to
promote the adoption of standards in
bioinformatics; the development of these standards
promotes data sharing.
Comprehensive data sets—Where several publicly
available repositories exist, we have negotiated
data-sharing agreements to ensure that our resources
are comprehensive and up-to-date. We also negoti-
ate with publishers to ensure that, wherever practi-
cable, biological data are placed in a public
repository as part of the publication process and
cross-referenced in the relevant publication.
Portability—If practical our datasets are available
for download. In many cases the entire software
system can be downloaded and installed locally.
Quality—Our databases are enhanced through anno-
tation: features of the objects stored in them are
extracted from other sources, defined and inter-
preted. Much of our annotation is performed by
highly qualified biologists, and automated annota-
tion is subjected to rigorous quality control. In
many cases we also exploit expertise outside of the
EBI for specialist annotation.
D18 Nucleic Acids Research, 2010, Vol. 38, Database issue
A natural reference point for biology
The genome is a concept at the heart of biology. Since the
first complete genome was sequenced in the mid 1990s,
over 1000 more have been sequenced, annotated and sub-
mitted to the public databases; but these represent only a
small proportion of the total number expected in the near
term. Ultra-high throughput sequencing technologies are
generating genome sequences at a rapidly accelerating
rate, both to gap-fill portions of the taxonomy where no
genome sequence has yet been deciphered and to generate
data for variation in populations of species of particular
interest. These technologies are also being used to generate
gene regulation and expression data on a genome-wide
The EMBL-EBI, in collaboration with the Wellcome
Trust Sanger Institute, developed the Ensembl Genome
Browser (6) in 2000. Ensembl’s original purpose was to
facilitate navigation and analysis of the human genome,
focusing on the annotation of known genes and predicting
the location of previously uncharacterised ones. This
methodology was extended to other important model
organisms, including brewer’s yeast and fruit fly. As the
list of sequenced organisms grew, a strategic decision was
taken to focus on chordates owing to their ability to help
us understand human biology and evolution. Over the
past 10 years, as the genomes of more organisms have
been sequenced, Ensembl’s coverage has grown to some
51 genomes. Year 2009 has witnessed addition of the first
reptile genome—that of the anole lizard—filling an impor-
tant evolutionary gap by adding the final vertebrate
class to Ensembl’s collection. Inter-species comparative
genomics experiments using the Ensembl system have
provided some important insights into previously over-
looked regions of the genome [for example, the discovery
that the human and chicken genomes shared large
stretches of conservation in non-coding regions (7)].
A unified view of the tree of life
The falling cost of genome sequencing makes it feasible
that the genomes of all species of significant scientific
interest will be sequenced in the near future, and that
projects to sequence many individuals of the same
species will follow. Such endeavours are already
underway for humans (,
Arabidopsis (8), Plasmodium (http://www.genome
.gov/26523588) and Drosophila (
One of the EMBL-EBI’s major achievements in 2009 has
been the successful application of the Ensembl system to
the rest of the taxonomic tree: Ensembl Genomes (9)
provides a companion service to Ensembl in the form of
five new sites: Ensembl Bacteria, Ensembl Protists,
Ensembl Fungi, Ensembl Plants and Ensembl Metazoa.
Ensembl Genomes replaces several pre-existing EMBL-
EBI resources (Integr8, Genome Reviews and ASTD),
thereby unifying services and simplifying data access for
users. The launch of Ensembl Genomes provides a consis-
tent framework for inter-species analyses across the whole
of taxonomic space.
A common set of user interfaces, including a graphical
genome browser, FTP, BLAST search, a query-optimised
data warehouse, programmatic access and a Perl API, is
provided for all domains, mirroring what was previously
available for vertebrates through Ensembl. Data types
incorporated include annotation of (protein and non-
protein coding) genes, cross-references to external
resources and high-throughput experimental data (for
example, data from large-scale studies of gene expression
and polymorphism visualised in their genomic context).
Pre-computed comparative analyses, both within defined
clades and across the wider taxonomy, and sequence
alignments and gene trees resulting from these are also
With such a broad scope, Ensembl Genomes is depen-
dent on the contribution of the scientific community; the
EBI can provide an infrastructure and a pan-taxonomic
perspective, but the biological expertise is widely
dispersed. Many of the databases within Ensembl
Genomes are produced by, or in close collaboration
with, specialist resources with domain-specific expertise
(WormBase, VectorBase and Gramene, for example),
and we are working actively to increase these relationships
as new species are introduced into the site.
From genotype to phenotype
Distinguishing the genetic differences between individuals
of the same species and linking these genotypic differences
to phenotypic differences provide important leads for
medical and agricultural research. The EMBL-EBI
launched the European Genome-phenome Archive
(EGA)—a repository for all types of potentially identifi-
able data types including the array-based genotype data
from genome-wide association studies—in July 2008. The
EGA stores the raw data from many types of experiments
including case control studies, cancer sequencing and pop-
ulation studies. Available data types include single
nucleotide polymorphism (SNP) and copy number varia-
tion (CNV) genotypes, whole genome sequence and
phenotype data. Each data type is stored at the EGA
using methods designed to ensure that the storage and
distribution is done in accordance with the consent and
confidentiality agreements that the research participants
agreed to at the time of entry into the study.
Coping with the deluge of next-generation sequencing data
Next-generation sequencing has led to previously
unimaginable amounts of data being deposited in the
public nucleotide sequence databases. The ENA has
been established (3) at the EBI to consolidate existing
major sequence resources, namely, the European
Trace Archive, previously maintained at the Wellcome
Trust Sanger Institute, the EMBL Nucleotide
Sequence Database (EMBL-Bank) and the Sequence
Read Archive (SRA), the newly established repository
for raw data from next generation sequencing platforms.
Significant technology developments at ENA have led to
improved submission and data access tools.
Nucleic Acids Research, 2010, Vol. 38, Database issue D19
The ENA comprises three parts: ENA-Annotation,
ENA-Assembly and ENA-Reads. ENA-Annotation
contains detailed functional annotation, for example of
individual, well characterised coding sequences. ENA-
Assembly is designed for efficient storage of sequence
assemblies. Finally, ENA-Reads is optimised for the effi-
cient storage of sequence trace information. These include
capillary trace sequences (the Trace Archive) and next-
generation reads (SRA, which is the fastest growing part
of the ENA). Entries from different data classes are con-
nected through high-level sample and project information.
A new, automated sequence-read submission tool
makes regular submission of next-generation sequencing
data very straightforward. For manual submissions
of annotated, assembled sequences, a template-based
sequence submission system has been developed.
Submitters can choose from a set of templates tailor-
made for each major annotation scenario, can upload
large-scale annotations prepared in third party annotation
tools, and can also design their own templates.
The most recent innovation in ENA is a newly launched
browser that provides integrated access to data from all
parts of ENA, including top-level project records, taxo-
nomic information, assembled sequence, functional anno-
tation, assembly information and metadata for trace and
next-generation reads. All accessions and many stored
fields have been made available for search through the
EB-eye search tool. Novel sequence similarity search
tools optimised for short reads delivered by next-
generation platforms are under development.
Genome-wide gene expression assays, originally using
microarrays and more recently high-throughput
sequencing, can either answer specific questions (for
example, which genes are differentially expressed in
healthy versus diseased liver) or provide reference data
sets (for example allowing gene expression patterns in dif-
ferent tissues, or at different developmental stages, to be
compared). Large-scale expression datasets can be used to
answer questions unrelated to the study for which the data
were originally generated. For example, a gene expression
study that reveals differentially expressed genes character-
istic of a particular type of cancer may also reveal candi-
date genes for therapeutics development, or shed light on
regulatory mechanisms perturbed in that form of cancer.
The ArrayExpress Archive was launched by the EMBL-
EBI in 2002 as the world’s first open-access, standards-
compliant repository for high-throughput transcriptomics
assays. In compliance with the MIAME initiative (10),
most scientific journals now require publication-related
microarray gene expression data to be deposited in
ArrayExpress (11) or the NCBI’s Gene Expression
Omnibus (GEO) (12). Data from over 10 000 studies are
available from these archives, but using these data to
answer biological questions is not straightforward.
The EMBL-EBI launched the Gene Expression Atlas
(GXA) (13) to simplify the analysis of gene expression
data. Users can pose gene-centric queries, to find out
under which conditions (or where in the organism) a
gene of interest is differentially expressed. Alternatively,
they can pose condition-centric queries, to find out
which genes are differentially expressed in a particular
condition or site. Both types of query can be combined
to focus on particular genes and their role in a specific
condition; for example, GXA makes it straightforward
to search for members of the Wnt signalling pathway
that are expressed in colorectal adenocarcinoma.
GXA takes a subset of the data from the ArrayExpress
Archive, including data imported from GEO (12) and
subjects it to rigorous curation. Mapping of genes to the
latest genome-builds ensures that each gene in GXA has
an unambiguous reference point. Mapping of conditions
to a purpose-built ontology—the Experimental Factor
Ontology (EFO) (11)—ensures that users retrieve all the
results relevant to their query, not just those that exactly
match the text of their query. More information on GXA
can be found in an e-learning tutorial at http://www.ebi.
UniProt (14) is the globally recognised ‘gold-standard’
data resource for information about proteins. UniProt is
produced by the UniProt Consortium, a collaboration
between the EMBL-EBI, the Swiss Institute of
Bioinformatics (SIB) and the Protein Information
Resource (PIR). The UniProt Knowledgebase, the
centrepiece of the UniProt Consortium’s activities,
provides an expertly and richly curated protein database
consisting of two sections: UniProtKB/Swiss-Prot
contains manually curated information on well-
characterised proteins and UniProtKB/TrEMBL
contains automatically annotated information on protein
sequences mostly sourced from the ENA (3).
As completely sequenced genomes have their full
complement of protein-coding genes characterised, it
becomes feasible to provide richly annotated complete
proteomes in UniProtKB/Swiss-Prot. A first draft of the
human proteome, comprising 20 325 protein-coding
sequences, was released in September 2008. This data set
has now been re-annotated to improve the depth and
quality of the information provided. New splice variants
and polymorphisms have been added to existing records,
and records have been created for newly discovered
protein sequences. UniProt has joined the Consensus
CDS (CCDS) project (15), a collaborative effort including
the Wellcome Trust Sanger Institute, the University of
California, Santa Cruz, the US National Center for
Biotechnology Information and the EMBL-EBI, to
identify a core set of consistently annotated and high-
quality human and mouse protein-coding regions. The
long-term goal is to support convergence towards a
standard set of gene and protein annotations.
The complete proteome for the fission yeast
Schizosaccharomyces pombe is also now available.
Comparison with the proteome of the evolutionarily
distant budding yeast, Saccharomyces cerevisiae,
provides a powerful tool for orthologue prediction.
D20 Nucleic Acids Research, 2010, Vol. 38, Database issue
Another innovation in UniProt is full cross-linking with
PRIDE (16), the EMBL-EBI’s standards-compliant
resource for mass spectrometry based proteomics. This
allows PRIDE submitters to improve the exposure of
their data, and allows PRIDE data to be used to
annotate UniProt protein entries.
The increasing number of publications on protein iden-
tification by mass-spectrometry provided the impetus for
the launch of PRIDE in 2005, and the PRIDE team has
worked closely with publishers to ensure that published
proteomics data are not lost to further analysis. For
instance, the submission process has now been made
much easier thanks to the new tool PRIDE Converter
(17). As a result, PRIDE is now the recommended sub-
mission point for proteomics data for several journals,
including Nature Biotechnology (18), Nature Methods
(19) and Proteomics. PRIDE is also a founding partner
of the ProteomExchange consortium (http://www. (20). The core members of this con-
sortium (PRIDE, NCBI Peptidome, Tranche,
PeptideAtlas and GPMDB) are working on a system to
allow proteomics data sharing between members of the
consortium, with PRIDE and NCBI Peptidome as the
initial ProteomExchange submission points. In addition
to the ProteomExchange initiative, PRIDE and NCBI
Peptidome have agreed to replicate and share their data,
to ensure that they become optimally visible to the scien-
tific community.
Protein families and domains are invaluable pointers
that help biologists to find distantly related proteins and
to predict their functions. A daunting array of resources,
each with different strengths and weaknesses, is available
to search genomes and proteomes for ‘protein
signatures’—diagnostic entities that are used to recogne
a particular domain or protein family. InterPro (21) is
an integrated documentation resource for protein
families, domains and functional sites. The member
databases of InterPro use different methods and types of
biological information to derive protein signatures from
well-charactered proteins. By uniting the member
databases, InterPro capitalises on their individual
strengths, producing a powerful integrated diagnostic
tool for protein sequence classification. In 2009, a new
member database joined the InterPro consortium and
was integrated into the resource: HAMAP (22) provides
high-quality automatic annotation of microbial proteomes
and complements the existing ten databases already con-
tained in InterPro, giving an in-depth perspective on
protein families from the prokaryotic and archaeal
kingdoms. Signatures from all member databases
continue to be integrated and the total number of entries
now stands at 19 170, an increase of just under 2500
signatures in the past year. InterPro has also launched a
BioMart (23) for more advanced querying of its data,
which includes web service access and links to other
BioMarts. Ensembl, UniProt, PDBe, Reactome and
PRIDE also have BioMarts, enabling advanced queries
to be performed across many of the EMBL-EBI’s core
data resources.
Structural biology has had an enormous impact on our
understanding of biology and medicine—as evidenced by
four Nobel Prizes awarded to workers in this field in this
century alone (2002, 2003, 2006, 2009). Three-dimensional
structures give us mechanistic insight into how
macromolecules work, and help to explain how their
functions are disrupted by mutation or interaction with
small molecules. As structural genomics efforts begin to
bear fruit (for example, the Midwest Center for Structural
Genomics deposited its 1000th structure in the PDB in
July 2009), the demand for efficient access to standard
ways of viewing and describing protein structures grows.
The Protein Databank in Europe (PDBe) (24), formerly
known as the Macromolecular Structure Database, is the
European partner of the worldwide Protein Databank
Organisation (wwPDB) (25), the other partners being the
Research Collaboratory for Structural Bioinformatics
(RCSB) (26) and the BioMagResBank (BMRB) (27) in
the USA, and the Protein Data Bank Japan (PDBj) (28).
wwPDB maintains the worldwide repository of bio-
macromolecular structure data.
Year 2009 witnessed the handover of the PDBe group’s
leadership to Gerard Kleywegt upon the retirement of
Kim Henrick. The tireless work of Kim and his team in
data remediation and automated analyses of structural
data have now been complemented by newly designed
PDBeView Atlas pages. These provide an overview of an
individual PDB entry in a user-friendly layout and serve as
a starting point to further explore the information avail-
able in the PDBe database. PDBe’s involvement with the
X-ray crystallography, Nuclear Magnetic Resonance spec-
troscopy and cryo-Electron Microscopy communities
have also resulted in improved tools for structure deposi-
tion and analysis.
As researchers look beyond the genome with the aim of
understanding all the processes of life, the need for a
public database of biologically relevant ‘small molecules’
(not directly encoded by the genome) grows increasingly
strong. ChEBI, the EMBL-EBI’s database of Chemical
Entities of Biological Interest (29), has been designed
with two aims in mind: first, to provide standard
descriptions of molecules that enable other databases to
annotate their entries consistently and second, to bridge
the gap between small molecules and the macromolecules
that they interact with in living systems. ChEBI is a freely
available, manually annotated database of small molecu-
lar entities. It focuses on chemical nomenclature and
structures, and provides a wide range of related chemical
data such as formulae, links to other databases and an
ontology for the chemical space.
ChEBI has grown 30-fold over the past two years.
Much of this growth is due to the ChEMBL dataset—a
large collection of information on the properties and
activities of drugs and a large set of drug-like small
molecules, which was transferred from the publicly listed
company Galapagos NV into the public domain in 2008,
Nucleic Acids Research, 2010, Vol. 38, Database issue D21
thanks to a substantial grant from the Wellcome Trust
(30). Other sources of new data in ChEBI include data
from the PDBeChem database—a library of ligands,
small molecules and monomers that are referenced in
PDB entries; and small molecules associated with
Patents, generated by the Oscar3 project in collaboration
with the European Patent Office. A small number of
entries have also been added through direct submissions,
and a web-based submission tool has been developed for
this purpose.
An important new feature of ChEBI is a chemical
structure-based search function, which uses a new algo-
rithm developed in the open source OrChem project (31).
A new text-search function has also been introduced.
Finally, ChEBI has greatly expanded its range of cross-
links to other databases, both within and beyond the
Computational systems biology today allows research
to move beyond the identification of molecular
‘parts lists’ for living organisms, towards synthesising
information from different omics-based approaches
to generate and test new hypotheses about how biologi-
cal systems work. Neither experimental nor computa-
tional biology alone will be sufficient to uncover a
systems-level understanding of biology. The ability to
analyse data from transcriptomics, proteomics, protein-
interaction studies, pathways and network analysis,
and infer how molecules function within systems, is
therefore becoming a required skill for experimental
biologists. Such analyses form the basis of new
Molecular interactions provide a valuable resource for
the elucidation of cellular function. IntAct provides a
central, public repository of such interactions, including
protein–protein, protein–small-molecule and protein–
nucleic-acid interations (32). IntAct is a member of The
International Molecular Exchange (IMEx) Consortium
( (33)—a group of public interaction
data providers that share curation effort and exchange
molecular interaction data, similarly to successful global
collaborations for protein and DNA sequences and
macromolecular structures. IntAct is also MIMIx compli-
ant, allowing researchers to submit their molecular inter-
action experiments in a format that complies with agreed
community standards (34).
Growth of the data in IntAct has necessitated a redesign
of its website, which now enables users to view pair-wise
interactions as a list before narrowing down their selection
criteria (for example, by choosing only those entries
for which there is the strongest experimental evidence)
and finally creating a graphical view of the selected
interactions. Chemical structure-based searching, using
the above-mentioned OrChem structure-based searching
algorithm (31), has also been introduced.
Life on the molecular level is an intricate network of
biochemical reactions and pathways. Biologists have been
elucidating fragments of this network for a century, but a
vast amount of the knowledge is scattered and largely
inaccessible to computational investigation. Straight-
forward computational access to this information is a pre-
requisite for systems biology. Reactome (35) goes some
way to satisfying this need as a free, online, open-source,
curated pathway database encompassing many areas of
human biology.
Reactome is a collaboration between the EMBL-EBI,
the Ontario Institute for Cancer Research, New York
University Medical Center and Cold Spring Harbor
Laboratory. Information is authored by expert biological
researchers, maintained by the Reactome editorial staff
and cross-referenced to a wide range of other
bioinformatics databases. The curated human data are
used to infer orthologous events in non-human species
including mouse, rat, chicken, puffer fish, worm, fly,
yeast, plants and Escherichia coli. Additions in 2009
have included a large number of cell signalling and
cell-adhesion pathways, and RNA metabolism; cross-
links are now provided to NCBI BioSystems, and
several species-centric research communities are using
the Reactome system to build their own species-specific
versions of Reactome, including gallus-Reactome and
Data in, knowledge out
Integrating biological data from different sources is the
holy grail of bioinformatics, and is made all the more
challenging by the fact that different levels of integration
are required for different types of task. The sheer volume
of data demands that they are structured for analysis by
computational pipelines, which, combined with the com-
plexity of the information, poses a substantial challenge.
Presenting the data and analyses to scientists in a compre-
hensible form is equally challenging.
The wealth of information available from the EMBL-
EBI website can be especially daunting for users unfamil-
iar with the core data resources. This is confounded by
the fact that many of our data resources are collaborative
efforts, with their own websites (e.g. http://www.ensembl.
The EB-eye search engine, available from every page of
the EMBL-EBI website, is designed to allow users to
perform text-based searches across the most commonly
used fields of all the EMBL-EBI’s core data resources,
without any prior knowledge of the underlying data
resources. The results are presented as an expandable list
of ‘knowledge domains’ covering different data types
(nucleotide sequences, protein sequences, macromolecules,
etc.). Each knowledge domain can then be expanded,
allowing the user to drill down into an individual
database, or even a single field in a specific database.
Extensive cross-linking between related objects in different
databases then allows navigation from one data resource
to another. More information about EB-eye can be
found at,
and there is an e-learning course on the EBeye at
D22 Nucleic Acids Research, 2010, Vol. 38, Database issue
The EB-eye is complemented by BioMart (23). Several
of the EMBL-EBI’s core data resources now have their
own BioMarts, and it’s possible to perform complex,
bespoke searches across several data resources using this
Databases and literature have been tightly connected
ever since the first biomolecular databases appeared.
Data records appearing in the databases cite the relevant
literature, and, for many kinds of data, the literature
quotes accession numbers or other identifiers in the
databases. The scientific literature provides a natural
entry point to the biomolecular databases, and we are
now beginning to exploit these connections through
CiteXplore, the EMBL-EBI’s portal to the literature.
CiteXplore uses text-mining tools developed by
researchers both within and beyond the EMBL-EBI to
mark up search results with links to many of the core
data resources.
Those who need to define their own analysis methods or
pipelines are supported by web services technology (36),
which allows users’ own programmes to interact with the
databases and tools at the EMBL-EBI. These web-services
interfaces can be used to retrieve and analyse large
amounts of data, or perform complex analyses that
involve several nested searches spanning a range of differ-
ent data resources. This provides an easy and flexible way
of dealing with repetitive tasks and large queries. Another
strength of web services is that they allow programmers to
build complex applications without having to install and
maintain the databases and analysis tools and without
having to take on the financial overheads that accompany
these. Moreover, web services provide easier integration
and interoperability between bioinformatics applications
and the data they require. A lightweight programme
(a client) on the user’s computer communicates with the
servers running at the EMBL-EBI. Users can create their
own clients or use the perl- and java-based clients that we
provide for each of our web services. Instructions on how
to build clients in a variety of programming languages can
be found in the tutorials at
European context: technical, scientific and political
The genomic era has changed research, by catalysing a
shift towards asking questions on a genome-wide scale
rather than one gene at a time. But perhaps even more
importantly, the genomic era heralded a social change
for the life-sciences: the scale of genome-sequencing
projects necessitated a completely open attitude towards
sharing data, both within and beyond the collaborative
groups involved in generating the sequence. Biological
experiments are now generating data at rates comparable
to astrophysics or particle physics experiments, and it all
has to be placed in the public domain and made amenable
to analysis by hundreds of thousands of researchers.
This requires an upgrade to the information infrastructure
of a scale and nature beyond the remit or capability of
conventional research funding mechanisms, both nation-
ally and internationally.
The European Strategy Forum on Research
Infrastructures (ESFRI,,
which advises the European Commission on Europe’s
future needs for research infrastructure, included a
major upgrade to Europe’s biological data infrastructure
in its 2005 Roadmap. The EMBL-EBI is coordinating
ELIXIR—a preparatory phase project that is preparing
the ground for building a new infrastructure for biol-
ogical data. ELIXIR will provide: data resources; bio-
compute centres; infrastructure for data integration,
software tools and services; support for other European
infrastructures in biomedical and environmental
research; training and standards development. This will
enable ELIXIR’s users to meet the European Grand
Challenges, the most important of which are biological,
namely: healthcare for an aging population, a sustain-
able food supply, competitive pharmaceutical and
biotechnology industries, and protection of the
ELIXIR will require financial support from all the
European Member states. Two countries—Sweden and
the UK—have already committed funds but there is still
a long way to go. Over the past 18 months, with significant
stakeholder input, ELIXIR’s workpackage committees
have written their recommendations for ELIXIR. These
are available at
php?page=reports, and we continue to welcome
feedback on them from our users, who are also vitally
important stakeholders. During the next part of
ELIXIR’s preparatory phase, these recommendations
will be incorporated into a business case which will lead
to the construction of ELIXIR beginning perhaps as early
as 2011.
The huge quantities of data that are now being
generated by life-science research provide unforeseen
opportunities and challenges. Already the new DNA
sequencing methods are providing the technology to
sequence individual genomes, to quantify expression, to
measure biodiversity and its response to the environment,
to study cancer differentiation and to measure a patient’s
responses to therapy to name but a few. Realising the
benefits of this knowledge to health and human wellbeing
will depend crucially on applying computational methods
to the vast repositories of data. Computational biology
will necessarily move to centre stage. Biological data
resources will lie at the heart of new discoveries and
their applications, and we must build the infrastructure
to support this endeavour. We firmly believe that this
infrastructure must remain rooted in the principles of
open access and international collaboration that have
enabled post-genomic research to progress at such an
impressive pace.
The EMBL-EBI is indebted to the support of its funders:
EMBL’s Member States, the European Commission, the
Wellcome Trust, the UK Research Councils, the US
Nucleic Acids Research, 2010, Vol. 38, Database issue D23
National Institutes of Health and our industry partners.
We are also indebted to hundreds of thousands of
scientists who have submitted data and annotation to
the shared data collections. The authors would like to
thank Guy Cochrane, Paul Flicek, Sarah Hunter, Paul
Kersey, Gerard Kleywegt, Claire O’Donovan and Juan
´no for their constructive feedback on this
Funding for open access charge: Wellcome Trust.
Conflict of interest statement. None declared.
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... Ever since then, biomedical informatics has unceasing advanced as a discipline encircling both medical informatics and bioinformatics as a result of the boundless number of research developments [14][15][16]. These developments comprise over a thousand public databases covering omics and disease information, which are vital to biomedical transformationalresearch [17][18][19][20][21][22].Note that biomedical informatics which started over seven decades has given rise to the development of more specialized but often interwoven areas to wit: chemical informatics, bioinformatics, health/medical informatics, nursing Informatics, and nanoinformatics. Nanoinformatics is a somewhat convergence of bioinformatics and cheminformatics [1] and designed to drive nanotechnology projects including drug discovery, design, modeling, clinical testing and delivery. ...
Full-text available
The world is witnessing sustained effects of information technologies across all works of life. Though some of these influences are markedly negative and detrimental to the socio-economic prospects and progress of the society, the positive effects are often impressive especially where they are integrated for the betterment and greater good of the larger society. One of the fastest growing technologies is nanotechnology. Nanotechnology has numerous prospects and applicability across various sectors ranging from electronics, telecommunications, agriculture and food production, biotechnology and genetics, oil prospecting and production, remote sensing, drug production, to name a few. This novel technology readily finds usefulness and several researches are ongoing, geared at developing new tools and techniques that would improve its acceptance across the concerned domains. It is this quest that has culminated into the ongoing effort in nanoinformatics, an interdisciplinary study and a subdomain of informatics simply regarded as the conscientious application of informatics tools and technologies to the analysis, design and development of systems on the broad spectrum of nanomaterials including their physicochemical and environmental characteristics as well as their interactions, interrelationships, and applications within a given domain. This paper presents a review of some opportunities for individuals, experts, and the society especially in the production of cost-effective nanotechnology-based healthcare products. Notwithstanding the aforesaid opportunities which could be harnessed and sustained in any developing country like Nigeria, this paper identifies and buttresses core challenges that could confront the adoption of good nanoinformatics methodologies. This paper concludes that a developing country (Nigeria in perspective) could benefit from nanoinformatics if there are stronger ties among the key stakeholders involved in healthcare products delivery in the society.
... Fields for metadata relevant to the dataset being submitted are listed in Table 3. The first three fields ('Species', 'Instrument', and 'Post-Translational Modifications') are backed by lists of standardized controlled vocabulary (CV) terms, maintained by organizations such as the HUPO Proteomics Standards Initiative 116 and many others, that the user can implement 116,117 . To search these terms, type at least three characters into any of these text boxes, and a drop-down list of supported terms that match your query will be displayed. ...
Global Natural Product Social Molecular Networking (GNPS) is an interactive online small molecule–focused tandem mass spectrometry (MS2) data curation and analysis infrastructure. It is intended to provide as much chemical insight as possible into an untargeted MS2 dataset and to connect this chemical insight to the user’s underlying biological questions. This can be performed within one liquid chromatography (LC)-MS2 experiment or at the repository scale. GNPS-MassIVE is a public data repository for untargeted MS2 data with sample information (metadata) and annotated MS2 spectra. These publicly accessible data can be annotated and updated with the GNPS infrastructure keeping a continuous record of all changes. This knowledge is disseminated across all public data; it is a living dataset. Molecular networking—one of the main analysis tools used within the GNPS platform—creates a structured data table that reflects the molecular diversity captured in tandem mass spectrometry experiments by computing the relationships of the MS2 spectra as spectral similarity. This protocol provides step-by-step instructions for creating reproducible, high-quality molecular networks. For training purposes, the reader is led through a 90- to 120-min procedure that starts by recalling an example public dataset and its sample information and proceeds to creating and interpreting a molecular network. Each data analysis job can be shared or cloned to disseminate the knowledge gained, thus propagating information that can lead to the discovery of molecules, metabolic pathways, and ecosystem/community interactions. Global Natural Product Social Molecular Networking (GNPS) is an online tandem mass spectrometry (MS2) data curation and analysis infrastructure. This protocol describes how to use GNPS to explore uploaded metabolomics data.
... The hard question of place for storing while useful to the workplace is depending on the size of each base. The DNA order size vary from Megabyte (MB) to Terabyte(TB) annually [2][3][4][5][6][7][8]. The DNA contains some logical organization [9], hence data structure for storing, accessing and efficient processing tasks is challenging [10][11]. ...
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Humans, by nature, have always been fascinated by the possibility of being able to acquire more information in minimum possible time and space. The effective lossless compression method, effective data structure, and DNA (Deoxyribonucleic Acid) data searching are quite essential as they provide a stimulus to easy accessibility and communication. The proposed algorithm is a new Lossless Compression algorithm, which compresses data, based on two tiers. Firstly, it searches for the exact Genetic Palindrome(GP), Palindrome(P) and Reverse(R)[GP2R] and the substring is reported, which is replaced by the corresponding ASCII character creating a Library file. By using the ASCII code, the Library file acts as a signature as well as provides the security of data. Secondly, modified RSA technique is proposed for the selection encryption purpose. This selection encryption of the modified RSA technique is an approach to lessen computational resources for greatly sized DNA facts. The experimental work shows 44% to 45% original sequence is encrypted where above 95% of the original file is damaged by using this method. This technique can find out the 3.851273 bits per base of the compression rate. The O(n) is the complexity of this algorithm. The running time is a few seconds of this algorithm. This is a hybrid approach to the compression & encryption process. For reducing the compression rate, the first pass output is again compressed by the second pass but it is lossy, This experiment is performed on benchmark DNA order.
... On the other hand, NGS techniques have introduced a new challenge in which a lot of DNA sequences have to be stored in various databases [11,12]. Large public databases for storing DNA sequences include the GenBank at the National Center for Biotechnology Information (NCBI) [13], the European Bioinformatics Institute EMBL database [14] and the DNA Data Bank of Japan (DDBJ) [15]. Records in these three databases are indeed synchronised so that each database contains a copy of the others. ...
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Due to the advancement of high‐throughput sequencing technologies, it is now feasible for sequencing individual genomes in a fast and affordable manner. With the significant increase in the number of individual genomes, compression methods are needed to reduce pressure on data storage as well as enable effective data distribution and management. The compression methods can generally be divided into two classes, namely reference‐free methods and reference‐based methods. In reference‐free methods, redundancies within the target DNA sequence to be compressed are explored. In reference‐based methods, redundancies between the target DNA sequence and other reference sequences are identified to achieve compression. This type of method is applicable to population sequences which are highly similar to each other and have a small number of mismatches. Some of the methods can also be applied to partially similar sequences such as chromosome sequences or sequences having evolutionary relationship. The authors highlight recent developments in these methods. In the comparative study, the authors’ simulation results reveal that the selection of a reference sequence is a crucial factor affecting the compression performance. Use of multiple number of reference sequences and enhancement strategies such as reference rewriting are important to achieve a large compression gain.
This chapter provides guidelines for developing a university library collection for bioinformatics programs. The chapter discusses current research and scholarly communication trends in bioinformatics and their impact on information needs and information seeking behavior of bioinformaticians and, consequently, on collection development. It also discusses the criteria for making collection development decisions that are largely influenced by the interdisciplinary nature of the field. The types of information resources most frequently used by bioinformaticians are described, specific resources are suggested, and creative options aimed at finding ways for a bioinformatics library collection to expand in the digital era are explored. The author draws on literature in bioinformatics and the library and information sciences as well as on her ten years of experience providing bioinformatics user services at George Mason University. The chapter is geared towards practicing librarians who are charged with developing a collection for bioinformatics academic programs as well as future librarians taking courses on collection development and academic librarianship.
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We introduce COnTORT ( CO mprehensive T ranscriptomic OR ganizational T ool), a publicly available program that retrieves all available gene expression data and associated metadata for an organism from the National Center for Biotechnology Information (NCBI) Gene Expression Omnibus (GEO) database. The data are compiled into text files that can be used for downstream bioinformatic applications.
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Herein, we present a protocol for the use of Global Natural Products Social (GNPS) Molecular Networking, an interactive online chemistry-focused mass spectrometry data curation and analysis infrastructure. The goal of GNPS is to provide as much chemical insight for an untargeted tandem mass spectrometry data set as possible and to connect this chemical insight to the underlying biological questions a user wishers to address. This can be performed within one experiment or at the repository scale. GNPS not only serves as a public data repository for untargeted tandem mass spectrometry data with the sample information (metadata), it also captures community knowledge that is disseminated via living data across all public data. One or the main analysis tools used by the GNPS community is molecular networking. Molecular networking creates a structured data table that reflects the chemical space from tandem mass spectrometry experiments via computing the relationships of the tandem mass spectra through spectral similarity. This protocol provides step-by-step instructions for creating reproducible high-quality molecular networks. For training purposes, the reader is led through the protocol from recalling a public data set and its sample information to creating and interpreting a molecular network. Each data analysis job can be shared or cloned to disseminate the knowledge gained, thus propagating information that can lead to the discovery of molecules, metabolic pathways, and ecosystem/community interactions.
Metabolic rewiring or reprogramming is the alteration of metabolism in living organisms, leading to disordered states aberrant from homeostasis. As large amounts of omics data become available, complex mechanisms leading to or driven by metabolic rewiring of cells can be better understood using reconstructed context-specific genome-scale metabolic models (GEMs). Here, we review recent advances in reconstructing context-specific GEMs for studying metabolic rewiring of human cells or tissues, from generic GEMs and omics databases to multiomics data integration methods. Also, we review recent studies that use context-specific GEMs to obtain insights such as identifying key regulators or therapeutic targets. Analyses of recent trends indicate the importance of integrating context-specific GEMs with multiscale networks for understanding metabolic diseases and advancing precision medicine.
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We present here a draft genome sequence of the red jungle fowl, Gallus gallus. Because the chicken is a modern descendant of the dinosaurs and the first non-mammalian amniote to have its genome sequenced, the draft sequence of its genome--composed of approximately one billion base pairs of sequence and an estimated 20,000-23,000 genes--provides a new perspective on vertebrate genome evolution, while also improving the annotation of mammalian genomes. For example, the evolutionary distance between chicken and human provides high specificity in detecting functional elements, both non-coding and coding. Notably, many conserved non-coding sequences are far from genes and cannot be assigned to defined functional classes. In coding regions the evolutionary dynamics of protein domains and orthologous groups illustrate processes that distinguish the lineages leading to birds and mammals. The distinctive properties of avian microchromosomes, together with the inferred patterns of conserved synteny, provide additional insights into vertebrate chromosome architecture.
Full-text available
We present here a draft genome sequence of the red jungle fowl, Gallus gallus. Because the chicken is a modern descendant of the dinosaurs and the first non-mammalian amniote to have its genome sequenced, the draft sequence of its genome--composed of approximately one billion base pairs of sequence and an estimated 20,000-23,000 genes--provides a new perspective on vertebrate genome evolution, while also improving the annotation of mammalian genomes. For example, the evolutionary distance between chicken and human provides high specificity in detecting functional elements, both non-coding and coding. Notably, many conserved non-coding sequences are far from genes and cannot be assigned to defined functional classes. In coding regions the evolutionary dynamics of protein domains and orthologous groups illustrate processes that distinguish the lineages leading to birds and mammals. The distinctive properties of avian microchromosomes, together with the inferred patterns of conserved synteny, provide additional insights into vertebrate chromosome architecture.
Full-text available
The primary mission of UniProt is to support biological research by maintaining a stable, comprehensive, fully classified, richly and accurately annotated protein sequence knowledgebase, with extensive cross-references and querying interfaces freely accessible to the scientific community. UniProt is produced by the UniProt Consortium which consists of groups from the European Bioinformatics Institute (EBI), the Swiss Institute of Bioinformatics (SIB) and the Protein Information Resource (PIR). UniProt is comprised of four major components, each optimized for different uses: the UniProt Archive, the UniProt Knowledgebase, the UniProt Reference Clusters and the UniProt Metagenomic and Environmental Sequence Database. UniProt is updated and distributed every 3 weeks and can be accessed online for searches or download at
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The Protein Data Bank in Europe (PDBe) ( is actively working with its Worldwide Protein Data Bank partners to enhance the quality and consistency of the international archive of bio-macromolecular structure data, the Protein Data Bank (PDB). PDBe also works closely with its collaborators at the European Bioinformatics Institute and the scientific community around the world to enhance its databases and services by adding curated and actively maintained derived data to the existing structural data in the PDB. We have developed a new database infrastructure based on the remediated PDB archive data and a specially designed database for storing information on interactions between proteins and bound molecules. The group has developed new services that allow users to carry out simple textual queries or more complex 3D structure-based queries. The newly designed ‘PDBeView Atlas pages’ provide an overview of an individual PDB entry in a user-friendly layout and serve as a starting point to further explore the information available in the PDBe database. PDBe’s active involvement with the X-ray crystallography, Nuclear Magnetic Resonance spectroscopy and cryo-Electron Microscopy communities have resulted in improved tools for structure deposition and analysis.
p>ArrayExpress consists of three components: the ArrayExpress Repository--a public archive of functional genomics experiments and supporting data, the ArrayExpress Warehouse--a database of gene expression profiles and other bio-measurements and the ArrayExpress Atlas--a new summary database and meta-analytical tool of ranked gene expression across multiple experiments and different biological conditions. The Repository contains data from over 6000 experiments comprising approximately 200,000 assays, and the database doubles in size every 15 months. The majority of the data are array based, but other data types are included, most recently-ultra high-throughput sequencing transcriptomics and epigenetic data. The Warehouse and Atlas allow users to query for differentially expressed genes by gene names and properties, experimental conditions and sample properties, or a combination of both. In this update, we describe the ArrayExpress developments over the last two years.</p
The mission of UniProt is to provide the scientific community with a comprehensive, high-quality and freely accessible resource of protein sequence and functional information that is essential for modern biological research. UniProt is produced by the UniProt Consortium which consists of groups from the European Bioinformatics Institute, the Protein Information Resource and the Swiss Institute of Bioinformatics. The core activities include manual curation of protein sequences assisted by computa-tional analysis, sequence archiving, a user-friendly UniProt website and the provision of additional value-added information through cross-references to other databases. UniProt is comprised of four major components, each optimized for different uses: the UniProt Archive, the UniProt Knowledge-base, the UniProt Reference Clusters and the Uni-Prot Metagenomic and Environmental Sequence Database. One of the key achievements of the UniProt consortium in 2008 is the completion of the first draft of the complete human proteome in UniProtKB/Swiss-Prot. This manually annotated representation of all currently known human protein-coding genes was made available in UniProt release 14.0 with 20 325 entries. UniProt is updated and distributed every three weeks and can be accessed online for searches or downloaded at INTRODUCTION
Philanthropic acquisition gives the academic chemogenomics community invaluable access to well-curated proprietary data.