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Holliday G.L.,EMBL EBI | Andreini C.,University of Florence | Fischer J.D.,EMBL EBI | Rahman S.A.,EMBL EBI | And 3 more authors.
Nucleic Acids Research | Year: 2012

MACiE (which stands for Mechanism, Annotation and Classification in Enzymes) is a database of enzyme reaction mechanisms, and can be accessed from http://www.ebi.ac.uk/thornton-srv/databases/ MACiE/. This article presents the release of Version 3 of MACiE, which not only extends the dataset to 335 entries, covering 182 of the EC sub-subclasses with a crystal structure available (∼90%), but also incorporates greater chemical and structural detail. This version of MACiE represents a shift in emphasis for new entries, from non-homologous representatives covering EC reaction space to enzymes with mechanisms of interest to our users and collaborators with a view to exploring the chemical diversity of life. We present new tools for exploring the data in MACiE and comparing entries as well as new analyses of the data and new searches, many of which can now be accessed via dedicated Perl scripts.


Dumousseau M.,EMBL EBI | Rodriguez N.,EMBL EBI | Juty N.,EMBL EBI | Novere N.L.,EMBL EBI
BMC Bioinformatics | Year: 2012

Background: Computing accurate nucleic acid melting temperatures has become a crucial step for the efficiency and the optimisation of numerous molecular biology techniques such as in situ hybridization, PCR, antigene targeting, and microarrays. MELTING is a free open source software which computes the enthalpy, entropy and melting temperature of nucleic acids. MELTING 4.2 was able to handle several types of hybridization such as DNA/DNA, RNA/RNA, DNA/RNA and provided corrections to melting temperatures due to the presence of sodium. The program can use either an approximative approach or a more accurate Nearest-Neighbor approach.Results: Two new versions of the MELTING software have been released. MELTING 4.3 is a direct update of version 4.2, integrating newly available thermodynamic parameters for inosine, a modified adenine base with an universal base capacity, and incorporates a correction for magnesium. MELTING 5 is a complete reimplementation which allows much greater flexibility and extensibility. It incorporates all the thermodynamic parameters and corrections provided in MELTING 4.x and introduces a large set of thermodynamic formulae and parameters, to facilitate the calculation of melting temperatures for perfectly matching sequences, mismatches, bulge loops, CNG repeats, dangling ends, inosines, locked nucleic acids, 2-hydroxyadenines and azobenzenes. It also includes temperature corrections for monovalent ions (sodium, potassium, Tris), magnesium ions and commonly used denaturing agents such as formamide and DMSO.Conclusions: MELTING is a useful and very flexible tool for predicting melting temperatures using approximative formulae or Nearest-Neighbor approaches, where one can select different sets of Nearest-Neighbor parameters, corrections and formulae. Both versions are freely available at http://sourceforge.net/projects/melting/and at http://www.ebi.ac.uk/compneur-srv/melting/under the terms of the GPL license. © 2012 Le Novère et al.; licensee BioMed Central Ltd.


Burge S.,EMBL EBI
Database : the journal of biological databases and curation | Year: 2012

InterPro amalgamates predictive protein signatures from a number of well-known partner databases into a single resource. To aid with interpretation of results, InterPro entries are manually annotated with terms from the Gene Ontology (GO). The InterPro2GO mappings are comprised of the cross-references between these two resources and are the largest source of GO annotation predictions for proteins. Here, we describe the protocol by which InterPro curators integrate GO terms into the InterPro database. We discuss the unique challenges involved in integrating specific GO terms with entries that may describe a diverse set of proteins, and we illustrate, with examples, how InterPro hierarchies reflect GO terms of increasing specificity. We describe a revised protocol for GO mapping that enables us to assign GO terms to domains based on the function of the individual domain, rather than the function of the families in which the domain is found. We also discuss how taxonomic constraints are dealt with and those cases where we are unable to add any appropriate GO terms. Expert manual annotation of InterPro entries with GO terms enables users to infer function, process or subcellular information for uncharacterized sequences based on sequence matches to predictive models. Database URL: http://www.ebi.ac.uk/interpro. The complete InterPro2GO mappings are available at: ftp://ftp.ebi.ac.uk/pub/databases/GO/goa/external2go/interpro2go.


Furnham N.,EMBL EBI | de Beer T.A.P.,EMBL EBI | Thornton J.M.,EMBL EBI
Current Opinion in Structural Biology | Year: 2012

With the huge volume in genomic sequences being generated from high-throughout sequencing projects the requirement for providing accurate and detailed annotations of gene products has never been greater. It is proving to be a huge challenge for computational biologists to use as much information as possible from experimental data to provide annotations for genome data of unknown function. A central component to this process is to use experimentally determined structures, which provide a means to detect homology that is not discernable from just the sequence and permit the consequences of genomic variation to be realized at the molecular level. In particular, structures also form the basis of many bioinformatics methods for improving the detailed functional annotations of enzymes in combination with similarities in sequence and chemistry. © 2012.


Rung J.,EMBL EBI
Nature reviews. Genetics | Year: 2013

Our understanding of gene expression has changed dramatically over the past decade, largely catalysed by technological developments. High-throughput experiments - microarrays and next-generation sequencing - have generated large amounts of genome-wide gene expression data that are collected in public archives. Added-value databases process, analyse and annotate these data further to make them accessible to every biologist. In this Review, we discuss the utility of the gene expression data that are in the public domain and how researchers are making use of these data. Reuse of public data can be very powerful, but there are many obstacles in data preparation and analysis and in the interpretation of the results. We will discuss these challenges and provide recommendations that we believe can improve the utility of such data.


Talavera D.,EMBL EBI | Taylor M.S.,EMBL EBI | Thornton J.M.,EMBL EBI
Proteins: Structure, Function and Bioinformatics | Year: 2010

The process of natural selection acts both on individual organisms within a population and on individual cells within an organism as they develop into cancer. In this work, we have taken a first step toward understanding the differences in selection pressures exerted on the human genome under these disparate circumstances. Focusing on single amino acid substitutions, we have found that cancer-related mutations (CRMs) are frequent in evolutionarily conserved sites, whereas single amino acid polymorphisms (SAPs) tend to appear in sites having a more relaxed evolutionary pressure. Those CRMs classed as cancer driver mutations show greater enrichment for conserved sites than passenger mutations. Consistent with this, driver mutations are enriched for sites annotated as key functional residues and their neighbors, and are more likely to be located on the surface of proteins than expected by chance. Overall the pattern of CRM and polymorphism is remarkably similar, but we do see a clear signal indicative of diversifying selection for disruptive amino acid substitutions in the cancer driver mutations. The ultimate consequence of the appearance of those mutations must be advantageous for the tumor cell, leading to cell population-growth and migration events similar to those seen in natural ecosystems. © 2009 Wiley-Liss, Inc.


McDowall J.,EMBL EBI
World Patent Information | Year: 2011

The European Bioinformatics Institute (EMBL-EBI) provides a free-access sequence search service that combines some of the most comprehensive, annotation-rich resources with a broad range of search and analysis tools. These resources contain patent abstracts, patent chemical compounds, patent sequences and patent equivalents extracted from the EPO, USPTO, JPO and KIPO, in addition to non-patent data. Patent protein and nucleotide sequence data are also available as annotation-enriched non-redundant datasets that clearly display priority dates. Search results are linked to a wide array of specialized databases and, for proteins, functional predictions that add in-depth annotation to help prioritize results when building a claim, without the need to search multiple databases. © 2011 Elsevier Ltd.


Bartonicek N.,EMBL EBI | Enright A.J.,EMBL EBI
Bioinformatics | Year: 2010

Summary: A useful step for understanding the function of microRNAs (miRNA) or siRNAs is the detection of their effects on genome-wide expression profiles. Typically, approaches look for enrichment of words in the 3'UTR sequences of the most deregulated genes. A number of tools are available for this purpose, but they require either in-depth computational knowledge, filtered 3'UTR sequences for the genome of interest, or a set of genes acquired through an arbitrary expression cutoff. To this end, we have developed SylArray; a web-based resource designed for the analysis of large-scale expression datasets. It simply requires the user to submit a sorted list of genes from an expression experiment. SylArray utilizes curated sets of 3'UTRs to attach sequences to these genes and then applies the Sylamer algorithm for detection of miRNA or siRNA signatures in those sequences. An intuitive system for visualization and interpretation of the small RNA signatures is included. © The Author 2010. Published by Oxford University Press. All rights reserved.


Fischer J.D.,EMBL EBI | Holliday G.L.,EMBL EBI | Thornton J.M.,EMBL EBI
Bioinformatics | Year: 2010

Motivation: Organic enzyme cofactors are involved in many enzyme reactions. Therefore, the analysis of cofactors is crucial to gain a better understanding of enzyme catalysis. To aid this, we have created the CoFactor database. Results: CoFactor provides a web interface to access hand-curated data extracted from the literature on organic enzyme cofactors in biocatalysis, as well as automatically collected information. CoFactor includes information on the conformational and solvent accessibility variation of the enzyme-bound cofactors, as well as mechanistic and structural information about the hosting enzymes. © The Author(s) 2010. Published by Oxford University Press.


Rung J.,EMBL EBI | Brazma A.,EMBL EBI
Nature Reviews Genetics | Year: 2013

Our understanding of gene expression has changed dramatically over the past decade, largely catalysed by technological developments. High-throughput experiments-microarrays and next-generation sequencing-have generated large amounts of genome-wide gene expression data that are collected in public archives. Added-value databases process, analyse and annotate these data further to make them accessible to every biologist. In this Review, we discuss the utility of the gene expression data that are in the public domain and how researchers are making use of these data. Reuse of public data can be very powerful, but there are many obstacles in data preparation and analysis and in the interpretation of the results. We will discuss these challenges and provide recommendations that we believe can improve the utility of such data. © 2013 Macmillan Publishers Limited. All rights reserved.

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