Annual Scientific Report 2015

Cheminformatics and Metabolism
Our team works on methods to decipher, organise and disseminate information
about the metabolism of organisms. We develop and maintain MetaboLights,
a metabolomics reference database and archive, and ChEBI, the database and
ontology of chemical entities of biological interest.
We develop algorithms to: process chemical information,
predict metabolomes based on genomic and other
information, determine the structure of metabolites
by stochastic screening of large candidate spaces, and
enable the identification of molecules with desired
properties. This requires algorithms based on machine
learning and other statistical methods for the prediction
of spectroscopic and other physicochemical properties
for compounds represented in chemical graphs.
Our research is dedicated to the elucidation of
metabolomes, Computer-Assisted Structure Elucidation
(CASE), the reconstruction of metabolic networks,
biomedical and biochemical ontologies and algorithm
development in cheminformatics and bioinformatics.
The chemical diversity of the metabolome and a lack of
accepted reporting standards currently make analysis
challenging and time-consuming. Part of our research
comprises the development and implementation of
methods to analyse spectroscopic data in metabolomics.
Major achievements
ChEBI
We added over 5 200 fully curated entries to the ChEBI
database during 2015 (total number of fully curated
entries, over 47 500). Around 30% of new entries are
from direct data submissions, and the remaining entries
are from a variety of sources. Our manual curation
concentrated on natural products, including compounds
identified in submissions to the MetaboLights database,
together with requests from individual users and
research groups. We also put considerable curation
efforts into the Species table, introduced to store
taxonomy and citation information for natural products,
which now contains over 11 000 entries.
On the ChEBI public website, we enhanced main entity
pages to allow users to view information about an entity
in a wider biological context. All biological reactions
and pathways in which the entity participates displayed
using Rhea and Reactome, respectively. ChEBI became
entirely open source (again) in 2015 when we replaced
the Marvin chemistry sketchpad (used for drawing
chemical structures when performing exact structure,
substructure, and similarity searches) with Ketcher.
From its first release in July 2004, ChEBI used
SourceForge as an issue tracker for logging and tracking
requests for new entries, updates to existing entries, new
feature requests, bugs and other queries. During 2015,
several press reports emerged regarding problems with
SourceForge, which gave rise to worries about its future
stability. In response to user requests, we migrated the
ChEBI issue tracker to GitHub as it offers advanced
features and flexibility.
MetaboLights
We developed new features to help researchers explore
the reference compounds, studies and associated
organism information in MetaboLights. These included
species search functionality based on model organisms,
free-text search and a browsable ‘tree of life’ with
automatic classification compatible with any taxonomic
identifier present in 89 different taxonomy sources.
We linked over 18 000 compounds in MetaboLights
to ChEBI, enriching compounds with 5355 spectra for
Mass Spectrometry and 2890 for NMR. MetaboLights
exported just over 150 datasets (265 total as of December
2015) to MetabolomeXchange, the global EBI Search
and the Omics Discovery Index.
In 2015 we completely redesigned MetaboLights to
accommodate a more flexible submission system,
which now supports incremental submissions.
The status of a study in our curation process is
now clearly visible. We also designed a new online
validation system that displays a detailed status of
our current minimum reporting requirements. We
incorporated new technology frameworks, for example
AngularJS, and built new Web Services. We worked on
integrating online analysis tools, for example adapting
MetaboAnalyst (David Wishart group, University of
Alberta). We incorporated tools into our architecture
using R packages and the EMBL-EBI R-cloud. In
tandem, we developed an authenticated Web Service
that enables improved visualisations and response time,
especially for larger datasets.
Community standards
The COSMOS consortium, an EU-funded endeavour
for the coordination of standards for metabolomics,
concluded its work in September 2015. The
consortium, led by our team, combined the efforts
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2015 EMBL-EBI Annual Scientific Report