One of the foundations of the scientific method is to be able to reproduce experiments and corroborate the results of research that has been done before. However, with the increasing complexities of new technologies and techniques, coupled with the specialisation of experiments, reproducing research findings has become a growing challenge. Clearly, scientific methods must be conveyed succinctly, and with clarity and rigour, in order for research to be reproducible. Here, we propose steps to help increase the transparency of the scientific method and the reproducibility of research results: specifically, we introduce a peer-review oath and accompanying manifesto. These have been designed to offer guidelines to enable reviewers (with the minimum friction or bias) to follow and apply open science principles, and support the ideas of transparency, reproducibility and ultimately greater societal impact. Introducing the oath and manifesto at the stage of peer review will help to check that the research being published includes everything that other researchers would need to successfully repeat the work. Peer review is the lynchpin of the publishing system: encouraging the community to consciously (and conscientiously) uphold these principles should help to improve published papers, increase confidence in the reproducibility of the work and, ultimately, provide strategic benefits to authors and their institutions.
One of the foundations of the scientific method is to be able to reproduce experiments and corroborate the results of research that has been done before. However, with the increasing complexities of new technologies and techniques, coupled with the specialisation of experiments, reproducing research findings has become a growing challenge. Clearly, scientific methods must be conveyed succinctly, and with clarity and rigour, in order for research to be reproducible. Here, we propose steps to help increase the transparency of the scientific method and the reproducibility of research results: specifically, we introduce a peer-review oath and accompanying manifesto. These have been designed to offer guidelines to enable reviewers (with the minimum friction or bias) to follow and apply open science principles, and support the ideas of transparency, reproducibility and ultimately greater societal impact. Introducing the oath and manifesto at the stage of peer review will help to check that the research being published includes everything that other researchers would need to successfully repeat the work. Peer review is the lynchpin of the publishing system: encouraging the community to consciously (and conscientiously) uphold these principles should help to improve published papers, increase confidence in the reproducibility of the work and, ultimately, provide strategic benefits to authors and their institutions. Future incarnations of the various national Research Excellence Frameworks (REFs) will evolve away from simple citations towards measurable societal value and impact. The proposed manifesto aspires to facilitate this goal by making transparency, reproducibility and citizen-scientist engagement (with the knowledge-creation and dissemination processes) the default parameters for performing sound research.
The PRINTS database, now in its 21st year, houses a collection of diagnostic protein family ‘fingerprints’. Fingerprints are groups of conserved motifs, evident in multiple sequence alignments, whose unique inter-relationships provide distinctive signatures for particular protein families and structural/functional domains. As such, they may be used to assign uncharacterized sequences to known families, and hence to infer tentative functional, structural and/or evolutionary relationships. The February 2012 release (version 42.0) includes 2156 fingerprints, encoding 12 444 individual motifs, covering a range of globular and membrane proteins, modular polypeptides and so on. Here, we report the current status of the database, and introduce a number of recent developments that help both to render a variety of our annotation and analysis tools easier to use and to make them more widely available.
Summary: Rapid technological advances have led to an explosion of biomedical data in recent years. The pace of change has inspired new collaborative approaches for sharing materials and resources to help train life scientists both in the use of cutting-edge bioinformatics tools and databases and in how to analyse and interpret large datasets. A prototype platform for sharing such training resources was recently created by the Bioinformatics Training Network (BTN). Building on this work, we have created a centralized portal for sharing training materials and courses, including a catalogue of trainers and course organizers, and an announcement service for training events. For course organizers, the portal provides opportunities to promote their training events; for trainers, the portal offers an environment for sharing materials, for gaining visibility for their work and promoting their skills; for trainees, it offers a convenient one-stop shop for finding suitable training resources and identifying relevant training events and activities locally and worldwide.
Availability and implementation:
With the continued growth in the volume both of experimental G protein-coupled receptor (GPCR) data and of the related peer-reviewed literature, the ability of GPCR researchers to keep up-to-date is becoming increasingly curtailed.
We present work that integrates the biological data and annotations in the GPCR information system (GPCRDB) with next-generation methods for intelligently exploring, visualising and interacting with the scientific articles used to disseminate them. This solution automatically retrieves relevant information from GPCRDB and displays it both within and as an adjunct to an article.
This approach allows researchers to extract more knowledge more swiftly from literature. Importantly, it allows reinterpretation of data in articles published before GPCR structure data became widely available, thereby rescuing these valuable data from long-dormant sources.
Regions of protein sequences with biased amino acid composition (so-called Low-Complexity Regions (LCRs)) are abundant in the protein universe. A number of studies have revealed that i) these regions show significant divergence across protein families; ii) the genetic mechanisms from which they arise lends them remarkable degrees of compositional plasticity. They have therefore proved difficult to compare using conventional sequence analysis techniques, and functions remain to be elucidated for most of them. Here we undertake a systematic investigation of LCRs in order to explore their possible functional significance, placed in the particular context of Protein-Protein Interaction (PPI) networks and Gene Ontology (GO)-term analysis.
In keeping with previous results, we found that LCR-containing proteins tend to have more binding partners across different PPI networks than proteins that have no LCRs. More specifically, our study suggests i) that LCRs are preferentially positioned towards the protein sequence extremities and, in contrast with centrally-located LCRs, such terminal LCRs show a correlation between their lengths and degrees of connectivity, and ii) that centrally-located LCRs are enriched with transcription-related GO terms, while terminal LCRs are enriched with translation and stress response-related terms.
Our results suggest not only that LCRs may be involved in flexible binding associated with specific functions, but also that their positions within a sequence may be important in determining both their binding properties and their biological roles.
We live in interesting times. Portents of impending catastrophe pervade the literature, calling us to action in the face of unmanageable volumes of scientific data. But it isn't so much data generation per se, but the systematic burial of the knowledge embodied in those data that poses the problem: there is so much information available that we simply no longer know what we know, and finding what we want is hard – too hard. The knowledge we seek is often fragmentary and disconnected, spread thinly across thousands of databases and millions of articles in thousands of journals. The intellectual energy required to search this array of data-archives, and the time and money this wastes, has led several researchers to challenge the methods by which we traditionally commit newly acquired facts and knowledge to the scientific record. We present some of these initiatives here – a whirlwind tour of recent projects to transform scholarly publishing paradigms, culminating in Utopia and the Semantic Biochemical Journal experiment. With their promises to provide new ways of interacting with the literature, and new and more powerful tools to access and extract the knowledge sequestered within it, we ask what advances they make and what obstacles to progress still exist? We explore these questions, and, as you read on, we invite you to engage in an experiment with us, a real-time test of a new technology to rescue data from the dormant pages of published documents. We ask you, please, to read the instructions carefully. The time has come: you may turn over your papers…
dynamic document content; interactive PDF; linking documents with research data; manuscript mark-up; mark-up standards; semantic publishing; BJ, Biochemical Journal; COHSE, Conceptual Open Hypermedia Services Environment; DOI, Digital Object Identifier; GO, Gene Ontology; GPCR, G protein-coupled receptor; HTML, HyperText Mark-up Language; IUPAC, International Union of Pure and Applied Chemistry; NTD, Neglected Tropical Diseases; OBO, Open Biomedical Ontologies; PDB, Protein Data Bank; PDF, Portable Document Format; PLoS, Public Library of Science; PMC, PubMed Central; PTM, post-translational modification; RSC, Royal Society of Chemistry; SDA, Structured Digital Abstract; STM, Scientific, Technical and Medical; UD, Utopia Documents; XML, eXtensible Mark-up Language; XMP, eXtensible Metadata Platform
In the biological sciences, the need to analyse vast amounts of information has become commonplace. Such large-scale analyses often involve drawing together data from a variety of different databases, held remotely on the internet or locally on in-house servers. Supporting these tasks are ad hoc collections of data-manipulation tools, scripting languages and visualisation software, which are often combined in arcane ways to create cumbersome systems that have been customised for a particular purpose, and are consequently not readily adaptable to other uses. For many day-to-day bioinformatics tasks, the sizes of current databases, and the scale of the analyses necessary, now demand increasing levels of automation; nevertheless, the unique experience and intuition of human researchers is still required to interpret the end results in any meaningful biological way. Putting humans in the loop requires tools to support real-time interaction with these vast and complex data-sets. Numerous tools do exist for this purpose, but many do not have optimal interfaces, most are effectively isolated from other tools and databases owing to incompatible data formats, and many have limited real-time performance when applied to realistically large data-sets: much of the user's cognitive capacity is therefore focused on controlling the software and manipulating esoteric file formats rather than on performing the research.
To confront these issues, harnessing expertise in human-computer interaction (HCI), high-performance rendering and distributed systems, and guided by bioinformaticians and end-user biologists, we are building reusable software components that, together, create a toolkit that is both architecturally sound from a computing point of view, and addresses both user and developer requirements. Key to the system's usability is its direct exploitation of semantics, which, crucially, gives individual components knowledge of their own functionality and allows them to interoperate seamlessly, removing many of the existing barriers and bottlenecks from standard bioinformatics tasks.
The toolkit, named Utopia, is freely available from .
The small leucine-rich repeat proteins and proteoglycans (SLRPs) form an important family of regulatory molecules that participate in many essential functions. They typically control the correct assembly of collagen fibrils, regulate mineral deposition in bone, and modulate the activity of potent cellular growth factors through many signalling cascades. SLRPs belong to the group of extracellular leucine-rich repeat proteins that are flanked at both ends by disulphide-bonded caps that protect the hydrophobic core of the terminal repeats. A capping motif specific to SLRPs has been recently described in the crystal structures of the core proteins of decorin and biglycan. This motif, designated as LRRCE, differs in both sequence and structure from other, more widespread leucine-rich capping motifs. To investigate if the LRRCE motif is a common structural feature found in other leucine-rich repeat proteins, we have defined characteristic sequence patterns and used them in genome-wide searches.
The LRRCE motif is a structural element exclusive to the main group of SLRPs. It appears to have evolved during early chordate evolution and is not found in protein sequences from non-chordate genomes. Our search has expanded the family of SLRPs to include new predicted protein sequences, mainly in fishes but with intriguing putative orthologs in mammals. The chromosomal locations of the newly predicted SLRP genes would support the large-scale genome or gene duplications that are thought to have occurred during vertebrate evolution. From this expanded list we describe a new class of SLRP sequences that could be representative of an ancestral SLRP gene.
Given its exclusivity the LRRCE motif is a useful annotation tool for the identification and classification of new SLRP sequences in genome databases. The expanded list of members of the SLRP family offers interesting insights into early vertebrate evolution and suggests an early chordate evolutionary origin for the LRRCE capping motif.
The mountains of data thrusting from the new landscape of modern high-throughput biology are irrevocably changing biomedical research and creating a near-insatiable demand for training in data management and manipulation and data mining and analysis. Among life scientists, from clinicians to environmental researchers, a common theme is the need not just to use, and gain familiarity with, bioinformatics tools and resources but also to understand their underlying fundamental theoretical and practical concepts. Providing bioinformatics training to empower life scientists to handle and analyse their data efficiently, and progress their research, is a challenge across the globe. Delivering good training goes beyond traditional lectures and resource-centric demos, using interactivity, problem-solving exercises and cooperative learning to substantially enhance training quality and learning outcomes. In this context, this article discusses various pragmatic criteria for identifying training needs and learning objectives, for selecting suitable trainees and trainers, for developing and maintaining training skills and evaluating training quality. Adherence to these criteria may help not only to guide course organizers and trainers on the path towards bioinformatics training excellence but, importantly, also to improve the training experience for life scientists.
bioinformatics; training; bioinformatics courses; training life scientists; train the trainers
The Eph (erythropoietin-producing hepatocellular carcinoma) B receptors are important in a variety of cellular processes through their roles in cell-to-cell contact and signalling; their up-regulation and down-regulation has been shown to have implications in a variety of cancers. A greater understanding of the similarities and differences within this small, highly conserved family of tyrosine kinases will be essential to the identification of effective therapeutic opportunities for disease intervention. In this study, we have developed a route to production of multi-milligram quantities of highly purified, homogeneous, recombinant protein for the kinase domain of these human receptors in Escherichia coli. Analyses of these isolated catalytic fragments have revealed stark contrasts in their amenability to recombinant expression and their physical properties: e.g., a >16°C variance in thermal stability, a 3-fold difference in catalytic activity and disparities in their inhibitor binding profiles. We find EphB3 to be an outlier in terms of both its intrinsic stability, and more importantly its ligand-binding properties. Our findings have led us to speculate about both their biological significance and potential routes for generating EphB isozyme-selective small-molecule inhibitors. Our comprehensive methodologies provide a template for similar in-depth studies of other kinase superfamily members.
EphB1; EphB2; EphB3; EphB4; kinase inhibition; protein stability; CMPD3, compound 3; DSF, differential scanning fluorimetry; DTT, dithiothreitol; Eph, erythropoietin-producing hepatocellular carcinoma; GdnHCl, guanidine hydrochloride; ITC, isothermal titration calorimetry; Ni-NTA, Ni2+-nitrilotriacetate; PTP1B, protein tyrosine phosphatase 1B; RTK, receptor tyrosine kinase; SEC, size-exclusion chromatography; TCEP, tris-(2-carboxyethyl)phosphine; TEV, tobacco etch virus; TFA, trifluoroacetic acid
Summary: We present iAnn, an open source community-driven platform for dissemination of life science events, such as courses, conferences and workshops. iAnn allows automatic visualisation and integration of customised event reports. A central repository lies at the core of the platform: curators add submitted events, and these are subsequently accessed via web services. Thus, once an iAnn widget is incorporated into a website, it permanently shows timely relevant information as if it were native to the remote site. At the same time, announcements submitted to the repository are automatically disseminated to all portals that query the system. To facilitate the visualization of announcements, iAnn provides powerful filtering options and views, integrated in Google Maps and Google Calendar. All iAnn widgets are freely available.
Curated databases are an integral part of the tool set that researchers use on a daily basis for their work. For most users, however, how databases are maintained, and by whom, is rather obscure. The International Society for Biocuration (ISB) represents biocurators, software engineers, developers and researchers with an interest in biocuration. Its goals include fostering communication between biocurators, promoting and describing their work, and highlighting the added value of biocuration to the world. The ISB recently conducted a survey of biocurators to better understand their educational and scientific backgrounds, their motivations for choosing a curatorial job and their career goals. The results are reported here. From the responses received, it is evident that biocuration is performed by highly trained scientists and perceived to be a stimulating career, offering both intellectual challenges and the satisfaction of performing work essential to the modern scientific community. It is also apparent that the ISB has at least a dual role to play to facilitate biocurators’ work: (i) to promote biocuration as a career within the greater scientific community; (ii) to aid the development of resources for biomedical research through promotion of nomenclature and data-sharing standards that will allow interconnection of biological databases and better exploit the pivotal contributions that biocurators are making.
Funding bodies are increasingly recognizing the need to provide graduates and researchers with access to short intensive courses in a variety of disciplines, in order both to improve the general skills base and to provide solid foundations on which researchers may build their careers. In response to the development of ‘high-throughput biology’, the need for training in the field of bioinformatics, in particular, is seeing a resurgence: it has been defined as a key priority by many Institutions and research programmes and is now an important component of many grant proposals. Nevertheless, when it comes to planning and preparing to meet such training needs, tension arises between the reward structures that predominate in the scientific community which compel individuals to publish or perish, and the time that must be devoted to the design, delivery and maintenance of high-quality training materials. Conversely, there is much relevant teaching material and training expertise available worldwide that, were it properly organized, could be exploited by anyone who needs to provide training or needs to set up a new course. To do this, however, the materials would have to be centralized in a database and clearly tagged in relation to target audiences, learning objectives, etc. Ideally, they would also be peer reviewed, and easily and efficiently accessible for downloading. Here, we present the Bioinformatics Training Network (BTN), a new enterprise that has been initiated to address these needs and review it, respectively, to similar initiatives and collections.
Bioinformatics; training; end users; bioinformatics courses; learning bioinformatics
InterPro (http://www.ebi.ac.uk/interpro/) is a database that integrates diverse information about protein families, domains and functional sites, and makes it freely available to the public via Web-based interfaces and services. Central to the database are diagnostic models, known as signatures, against which protein sequences can be searched to determine their potential function. InterPro has utility in the large-scale analysis of whole genomes and meta-genomes, as well as in characterizing individual protein sequences. Herein we give an overview of new developments in the database and its associated software since 2009, including updates to database content, curation processes and Web and programmatic interfaces.
The NucleaRDB is a Molecular Class-Specific Information System that collects, combines, validates and disseminates large amounts of heterogeneous data on nuclear hormone receptors. It contains both experimental and computationally derived data. The data and knowledge present in the NucleaRDB can be accessed using a number of different interactive and programmatic methods and query systems. A nuclear hormone receptor-specific PDF reader interface is available that can integrate the contents of the NucleaRDB with full-text scientific articles. The NucleaRDB is freely available at http://www.receptors.org/nucleardb.
The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources; and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological databases.
The present article proposes the adoption of a community-defined, uniform, generic description of the core attributes of biological databases, BioDBCore. The goals of these attributes are to provide a general overview of the database landscape, to encourage consistency and interoperability between resources and to promote the use of semantic and syntactic standards. BioDBCore will make it easier for users to evaluate the scope and relevance of available resources. This new resource will increase the collective impact of the information present in biological databases.
The EMBRACE (European Model for Bioinformatics Research and Community Education) web service collection is the culmination of a 5-year project that set out to investigate issues involved in developing and deploying web services for use in the life sciences. The project concluded that in order for web services to achieve widespread adoption, standards must be defined for the choice of web service technology, for semantically annotating both service function and the data exchanged, and a mechanism for discovering services must be provided. Building on this, the project developed: EDAM, an ontology for describing life science web services; BioXSD, a schema for exchanging data between services; and a centralized registry (http://www.embraceregistry.net) that collects together around 1000 services developed by the consortium partners. This article presents the current status of the collection and its associated recommendations and standards definitions.
Aspergillus Genomes is a public resource for viewing annotated genes predicted by various Aspergillus sequencing projects. It has arisen from the union of two significant resources: the Aspergillus/Aspergillosis website and the Central Aspergillus Data REpository (CADRE). The former has primarily served the medical community, providing information about Aspergillus and associated diseases to medics, patients and scientists; the latter has focused on the fungal genomic community, providing a central repository for sequences and annotation extracted from Aspergillus Genomes. By merging these databases, genomes benefit from extensive cross-linking with medical information to create a unique resource, spanning genomics and clinical aspects of the genus. Aspergillus Genomes is accessible from http://www.aspergillus-genomes.org.uk.
The InterPro database (http://www.ebi.ac.uk/interpro/) integrates together predictive models or ‘signatures’ representing protein domains, families and functional sites from multiple, diverse source databases: Gene3D, PANTHER, Pfam, PIRSF, PRINTS, ProDom, PROSITE, SMART, SUPERFAMILY and TIGRFAMs. Integration is performed manually and approximately half of the total ∼58 000 signatures available in the source databases belong to an InterPro entry. Recently, we have started to also display the remaining un-integrated signatures via our web interface. Other developments include the provision of non-signature data, such as structural data, in new XML files on our FTP site, as well as the inclusion of matchless UniProtKB proteins in the existing match XML files. The web interface has been extended and now links out to the ADAN predicted protein–protein interaction database and the SPICE and Dasty viewers. The latest public release (v18.0) covers 79.8% of UniProtKB (v14.1) and consists of 16 549 entries. InterPro data may be accessed either via the web address above, via web services, by downloading files by anonymous FTP or by using the InterProScan search software (http://www.ebi.ac.uk/Tools/InterProScan/).
InterPro is an integrated resource for protein families, domains and functional sites, which integrates the following protein signature databases: PROSITE, PRINTS, ProDom, Pfam, SMART, TIGRFAMs, PIRSF, SUPERFAMILY, Gene3D and PANTHER. The latter two new member databases have been integrated since the last publication in this journal. There have been several new developments in InterPro, including an additional reading field, new database links, extensions to the web interface and additional match XML files. InterPro has always provided matches to UniProtKB proteins on the website and in the match XML file on the FTP site. Additional matches to proteins in UniParc (UniProt archive) are now available for download in the new match XML files only. The latest InterPro release (13.0) contains more than 13 000 entries, covering over 78% of all proteins in UniProtKB. The database is available for text- and sequence-based searches via a webserver (), and for download by anonymous FTP (). The InterProScan search tool is now also available via a web service at .
Based on Bayesian Networks, methods were created that address protein sequence-based bacterial subcellular location prediction. Distinct predictive
algorithms for the eight bacterial subcellular locations were created. Several variant methods were explored. These variations included differences in
the number of residues considered within the query sequence - which ranged from the N-terminal 10 residues to the whole sequence - and residue representation -
which took the form of amino acid composition, percentage amino acid composition, or normalised amino acid composition. The accuracies of the best performing
networks were then compared to PSORTB. All individual location methods outperform PSORTB except for the Gram+ cytoplasmic protein predictor, for which accuracies
were essentially equal, and for outer membrane protein prediction, where PSORTB outperforms the binary predictor. The method described here is an important new
approach to method development for subcellular location prediction. It is also a new, potentially valuable tool for candidate subunit vaccine selection.
Bayesian networks; prediction method; subcellular location; membrane protein; periplasmic protein; secreted protein