Network


Latest external collaboration on country level. Dive into details by clicking on the dots.

Hotspot


Dive into the research topics where Paula de Matos is active.

Publication


Featured researches published by Paula de Matos.


Nucleic Acids Research | 2007

ChEBI: a database and ontology for chemical entities of biological interest

Kirill Degtyarenko; Paula de Matos; Marcus Ennis; Janna Hastings; Martin Zbinden; Alan McNaught; Rafael Alcántara; Michael Darsow; Mickaël Guedj; Michael Ashburner

Chemical Entities of Biological Interest (ChEBI) is a freely available dictionary of molecular entities focused on ‘small’ chemical compounds. The molecular entities in question are either natural products or synthetic products used to intervene in the processes of living organisms. Genome-encoded macromolecules (nucleic acids, proteins and peptides derived from proteins by cleavage) are not as a rule included in ChEBI. In addition to molecular entities, ChEBI contains groups (parts of molecular entities) and classes of entities. ChEBI includes an ontological classification, whereby the relationships between molecular entities or classes of entities and their parents and/or children are specified. ChEBI is available online at http://www.ebi.ac.uk/chebi/


Nucleic Acids Research | 2012

The ChEBI reference database and ontology for biologically relevant chemistry: enhancements for 2013

Janna Hastings; Paula de Matos; Adriano Dekker; Marcus Ennis; Bhavana Harsha; Namrata Kale; Venkatesh Muthukrishnan; Gareth Owen; Steve Turner; Mark A. Williams; Christoph Steinbeck

ChEBI (http://www.ebi.ac.uk/chebi) is a database and ontology of chemical entities of biological interest. Over the past few years, ChEBI has continued to grow steadily in content, and has added several new features. In addition to incorporating all user-requested compounds, our annotation efforts have emphasized immunology, natural products and metabolites in many species. All database entries are now ‘is_a’ classified within the ontology, meaning that all of the chemicals are available to semantic reasoning tools that harness the classification hierarchy. We have completely aligned the ontology with the Open Biomedical Ontologies (OBO) Foundry-recommended upper level Basic Formal Ontology. Furthermore, we have aligned our chemical classification with the classification of chemical-involving processes in the Gene Ontology (GO), and as a result of this effort, the majority of chemical-involving processes in GO are now defined in terms of the ChEBI entities that participate in them. This effort necessitated incorporating many additional biologically relevant compounds. We have incorporated additional data types including reference citations, and the species and component for metabolites. Finally, our website and web services have had several enhancements, most notably the provision of a dynamic new interactive graph-based ontology visualization.


Nucleic Acids Research | 2013

MetaboLights—an open-access general-purpose repository for metabolomics studies and associated meta-data

Kenneth Haug; Reza M. Salek; Pablo Conesa; Janna Hastings; Paula de Matos; Mark Rijnbeek; Tejasvi Mahendraker; Mark A. Williams; Steffen Neumann; Philippe Rocca-Serra; Eamonn Maguire; Alejandra Gonzalez-Beltran; Susanna-Assunta Sansone; Julian L. Griffin; Christoph Steinbeck

MetaboLights (http://www.ebi.ac.uk/metabolights) is the first general-purpose, open-access repository for metabolomics studies, their raw experimental data and associated metadata, maintained by one of the major open-access data providers in molecular biology. Metabolomic profiling is an important tool for research into biological functioning and into the systemic perturbations caused by diseases, diet and the environment. The effectiveness of such methods depends on the availability of public open data across a broad range of experimental methods and conditions. The MetaboLights repository, powered by the open source ISA framework, is cross-species and cross-technique. It will cover metabolite structures and their reference spectra as well as their biological roles, locations, concentrations and raw data from metabolic experiments. Studies automatically receive a stable unique accession number that can be used as a publication reference (e.g. MTBLS1). At present, the repository includes 15 submitted studies, encompassing 93 protocols for 714 assays, and span over 8 different species including human, Caenorhabditis elegans, Mus musculus and Arabidopsis thaliana. Eight hundred twenty-seven of the metabolites identified in these studies have been mapped to ChEBI. These studies cover a variety of techniques, including NMR spectroscopy and mass spectrometry.


Nucleic Acids Research | 2010

Chemical Entities of Biological Interest: an update

Paula de Matos; Rafael Alcántara; Adriano Dekker; Marcus Ennis; Janna Hastings; Kenneth Haug; Inmaculada Spiteri; Steve Turner; Christoph Steinbeck

Chemical Entities of Biological Interest (ChEBI) is a freely available dictionary of molecular entities focused on ‘small’ chemical compounds. The molecular entities in question are either natural products or synthetic products used to intervene in the processes of living organisms. Genome-encoded macromolecules (nucleic acids, proteins and peptides derived from proteins by cleavage) are not as a rule included in ChEBI. In addition to molecular entities, ChEBI contains groups (parts of molecular entities) and classes of entities. ChEBI includes an ontological classification, whereby the relationships between molecular entities or classes of entities and their parents and/or children are specified. ChEBI is available online at http://www.ebi.ac.uk/chebi/. This article reports on new features in ChEBI since the last NAR report in 2007, including substructure and similarity searching, a submission tool for authoring of ChEBI datasets by the community and a 30-fold increase in the number of chemical structures stored in ChEBI.


Nucleic Acids Research | 2012

Rhea—a manually curated resource of biochemical reactions

Rafael Alcántara; Kristian B. Axelsen; Anne Morgat; Eugeni Belda; Elisabeth Coudert; Alan Bridge; Hong Cao; Paula de Matos; Marcus Ennis; Steve Turner; Gareth Owen; Lydie Bougueleret; Ioannis Xenarios; Christoph Steinbeck

Rhea (http://www.ebi.ac.uk/rhea) is a comprehensive resource of expert-curated biochemical reactions. Rhea provides a non-redundant set of chemical transformations for use in a broad spectrum of applications, including metabolic network reconstruction and pathway inference. Rhea includes enzyme-catalyzed reactions (covering the IUBMB Enzyme Nomenclature list), transport reactions and spontaneously occurring reactions. Rhea reactions are described using chemical species from the Chemical Entities of Biological Interest ontology (ChEBI) and are stoichiometrically balanced for mass and charge. They are extensively manually curated with links to source literature and other public resources on metabolism including enzyme and pathway databases. This cross-referencing facilitates the mapping and reconciliation of common reactions and compounds between distinct resources, which is a common first step in the reconstruction of genome scale metabolic networks and models.


Current protocols in human genetics | 2009

ChEBI: An Open Bioinformatics and Cheminformatics Resource

Kirill Degtyarenko; Janna Hastings; Paula de Matos; Marcus Ennis

Chemical Entities of Biological Interest (ChEBI) is a freely available dictionary of molecular entities focused on “small” chemical compounds. This unit provides a detailed guide to browsing, searching, downloading, and programmatic access to the ChEBI database. Curr. Protoc. Bioinform. 26:14.9.1‐14.9.20.


PLOS Computational Biology | 2012

Bioinformatics meets user-centred design: a perspective.

Katrina Pavelin; Jennifer A. Cham; Paula de Matos; Catherine Brooksbank; Graham Cameron; Christoph Steinbeck

Designers have a saying that “the joy of an early release lasts but a short time. The bitterness of an unusable system lasts for years.” It is indeed disappointing to discover that your data resources are not being used to their full potential. Not only have you invested your time, effort, and research grant on the project, but you may face costly redesigns if you want to improve the system later. This scenario would be less likely if the product was designed to provide users with exactly what they need, so that it is fit for purpose before its launch. We work at EMBL-European Bioinformatics Institute (EMBL-EBI), and we consult extensively with life science researchers to find out what they need from biological data resources. We have found that although users believe that the bioinformatics community is providing accurate and valuable data, they often find the interfaces to these resources tricky to use and navigate. We believe that if you can find out what your users want even before you create the first mock-up of a system, the final product will provide a better user experience. This would encourage more people to use the resource and they would have greater access to the data, which could ultimately lead to more scientific discoveries. In this paper, we explore the need for a user-centred design (UCD) strategy when designing bioinformatics resources and illustrate this with examples from our work at EMBL-EBI. Our aim is to introduce the reader to how selected UCD techniques may be successfully applied to software design for bioinformatics.


BMC Genomics | 2013

Dovetailing biology and chemistry: integrating the Gene Ontology with the ChEBI chemical ontology

David P. Hill; Nico Adams; Mike Bada; Colin R. Batchelor; Tanya Z. Berardini; Heiko Dietze; Harold J. Drabkin; Marcus Ennis; Rebecca E. Foulger; Midori A. Harris; Janna Hastings; Namrata Kale; Paula de Matos; Christopher J. Mungall; Gareth Owen; Paola Roncaglia; Christoph Steinbeck; Steve Turner; Jane Lomax

BackgroundThe Gene Ontology (GO) facilitates the description of the action of gene products in a biological context. Many GO terms refer to chemical entities that participate in biological processes. To facilitate accurate and consistent systems-wide biological representation, it is necessary to integrate the chemical view of these entities with the biological view of GO functions and processes. We describe a collaborative effort between the GO and the Chemical Entities of Biological Interest (ChEBI) ontology developers to ensure that the representation of chemicals in the GO is both internally consistent and in alignment with the chemical expertise captured in ChEBI.ResultsWe have examined and integrated the ChEBI structural hierarchy into the GO resource through computationally-assisted manual curation of both GO and ChEBI. Our work has resulted in the creation of computable definitions of GO terms that contain fully defined semantic relationships to corresponding chemical terms in ChEBI.ConclusionsThe set of logical definitions using both the GO and ChEBI has already been used to automate aspects of GO development and has the potential to allow the integration of data across the domains of biology and chemistry. These logical definitions are available as an extended version of the ontology from http://purl.obolibrary.org/obo/go/extensions/go-plus.owl.


Methods of Molecular Biology | 2012

A Database for Chemical Proteomics: ChEBI

Paula de Matos; Nico Adams; Janna Hastings; Pablo Moreno; Christoph Steinbeck

Chemical proteomics is concerned with the identification of protein targets interacting with small molecules. Hence, the availability of a high quality and free resource storing small molecules is essential for the future development of the field. The Chemical Entities of Biological Interest (ChEBI) database is one such database. The scope of ChEBI includes any constitutionally or isotopically distinct atom, molecule, ion, ion pair, radical, radical ion, complex, conformer, etc., identifiable as a separately distinguishable entity. These entities in question are either products of nature or synthetic products used to intervene in the processes of living organisms. In addition, ChEBI contains a chemical ontology which relates the small molecules with each other thereby making it easier for users to discover data. The ontology also describes the biological roles that the small molecules are active in. The ChEBI database also provides a central reference point in which to access a variety of bioinformatics data points such as pathways and their biochemical reactions; expression data; protein sequence and structures.


BMC Bioinformatics | 2013

The Enzyme Portal: a case study in applying user-centred design methods in bioinformatics

Paula de Matos; Jennifer A. Cham; Hong Cao; Rafael Alcántara; Francis Rowland; Rodrigo Lopez; Christoph Steinbeck

User-centred design (UCD) is a type of user interface design in which the needs and desires of users are taken into account at each stage of the design process for a service or product; often for software applications and websites. Its goal is to facilitate the design of software that is both useful and easy to use. To achieve this, you must characterise users’ requirements, design suitable interactions to meet their needs, and test your designs using prototypes and real life scenarios.For bioinformatics, there is little practical information available regarding how to carry out UCD in practice. To address this we describe a complete, multi-stage UCD process used for creating a new bioinformatics resource for integrating enzyme information, called the Enzyme Portal (http://www.ebi.ac.uk/enzymeportal). This freely-available service mines and displays data about proteins with enzymatic activity from public repositories via a single search, and includes biochemical reactions, biological pathways, small molecule chemistry, disease information, 3D protein structures and relevant scientific literature.We employed several UCD techniques, including: persona development, interviews, ‘canvas sort’ card sorting, user workflows, usability testing and others. Our hope is that this case study will motivate the reader to apply similar UCD approaches to their own software design for bioinformatics. Indeed, we found the benefits included more effective decision-making for design ideas and technologies; enhanced team-working and communication; cost effectiveness; and ultimately a service that more closely meets the needs of our target audience.

Collaboration


Dive into the Paula de Matos's collaboration.

Top Co-Authors

Avatar

Christoph Steinbeck

European Bioinformatics Institute

View shared research outputs
Top Co-Authors

Avatar

Janna Hastings

European Bioinformatics Institute

View shared research outputs
Top Co-Authors

Avatar

Steve Turner

European Bioinformatics Institute

View shared research outputs
Top Co-Authors

Avatar

Marcus Ennis

Swiss Institute of Bioinformatics

View shared research outputs
Top Co-Authors

Avatar

Adriano Dekker

European Bioinformatics Institute

View shared research outputs
Top Co-Authors

Avatar

Gareth Owen

European Bioinformatics Institute

View shared research outputs
Top Co-Authors

Avatar

Kenneth Haug

European Bioinformatics Institute

View shared research outputs
Top Co-Authors

Avatar

Marcus Ennis

Swiss Institute of Bioinformatics

View shared research outputs
Top Co-Authors

Avatar

Rafael Alcántara

European Bioinformatics Institute

View shared research outputs
Top Co-Authors

Avatar

Zara Josephs

European Bioinformatics Institute

View shared research outputs
Researchain Logo
Decentralizing Knowledge