PMCC PMCC

Search tips
Search criteria

Advanced
Results 1-16 (16)
 

Clipboard (0)
None

Select a Filter Below

Journals
Year of Publication
Document Types
1.  KEGGViewer, a BioJS component to visualize KEGG Pathways 
F1000Research  2014;3:43.
Summary: Signaling pathways provide essential information on complex regulatory processes within the cell. They are moreover widely used to interpret and integrate data from large-scale studies, such as expression or functional screens. We present KEGGViewer a BioJS component to visualize KEGG pathways and to allow their visual integration with functional data.
Availability: KEGGViewer is an open-source tool freely available at the BioJS Registry. Instructions on how to use the tool are available at http://goo.gl/dVeWpg and the source code can be found at http://github.com/biojs/biojs and DOI: 10.5281/zenodo.7708.
doi:10.12688/f1000research.3-43.v1
PMCID: PMC3954160
2.  Best practices in bioinformatics training for life scientists 
Briefings in Bioinformatics  2013;14(5):528-537.
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.
doi:10.1093/bib/bbt043
PMCID: PMC3771230  PMID: 23803301
bioinformatics; training; bioinformatics courses; training life scientists; train the trainers
3.  iAnn: an event sharing platform for the life sciences 
Bioinformatics  2013;29(15):1919-1921.
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.
Availability: http://iann.pro/iannviewer
Contact: manuel.corpas@tgac.ac.uk
doi:10.1093/bioinformatics/btt306
PMCID: PMC3712218  PMID: 23742982
4.  A new reference implementation of the PSICQUIC web service 
Nucleic Acids Research  2013;41(Web Server issue):W601-W606.
The Proteomics Standard Initiative Common QUery InterfaCe (PSICQUIC) specification was created by the Human Proteome Organization Proteomics Standards Initiative (HUPO-PSI) to enable computational access to molecular-interaction data resources by means of a standard Web Service and query language. Currently providing >150 million binary interaction evidences from 28 servers globally, the PSICQUIC interface allows the concurrent search of multiple molecular-interaction information resources using a single query. Here, we present an extension of the PSICQUIC specification (version 1.3), which has been released to be compliant with the enhanced standards in molecular interactions. The new release also includes a new reference implementation of the PSICQUIC server available to the data providers. It offers augmented web service capabilities and improves the user experience. PSICQUIC has been running for almost 5 years, with a user base growing from only 4 data providers to 28 (April 2013) allowing access to 151 310 109 binary interactions. The power of this web service is shown in PSICQUIC View web application, an example of how to simultaneously query, browse and download results from the different PSICQUIC servers. This application is free and open to all users with no login requirement (http://www.ebi.ac.uk/Tools/webservices/psicquic/view/main.xhtml).
doi:10.1093/nar/gkt392
PMCID: PMC3977660  PMID: 23671334
5.  Teaching the Fundamentals of Biological Data Integration Using Classroom Games 
PLoS Computational Biology  2012;8(12):e1002789.
This article aims to introduce the nature of data integration to life scientists. Generally, the subject of data integration is not discussed outside the field of computational science and is not covered in any detail, or even neglected, when teaching/training trainees. End users (hereby defined as wet-lab trainees, clinicians, lab researchers) will mostly interact with bioinformatics resources and tools through web interfaces that mask the user from the data integration processes. However, the lack of formal training or acquaintance with even simple database concepts and terminology often results in a real obstacle to the full comprehension of the resources and tools the end users wish to access. Understanding how data integration works is fundamental to empowering trainees to see the limitations as well as the possibilities when exploring, retrieving, and analysing biological data from databases. Here we introduce a game-based learning activity for training/teaching the topic of data integration that trainers/educators can adopt and adapt for their classroom. In particular we provide an example using DAS (Distributed Annotation Systems) as a method for data integration.
doi:10.1371/journal.pcbi.1002789
PMCID: PMC3531283  PMID: 23300402
6.  MyDas, an Extensible Java DAS Server 
PLoS ONE  2012;7(9):e44180.
A large number of diverse, complex, and distributed data resources are currently available in the Bioinformatics domain. The pace of discovery and the diversity of information means that centralised reference databases like UniProt and Ensembl cannot integrate all potentially relevant information sources. From a user perspective however, centralised access to all relevant information concerning a specific query is essential. The Distributed Annotation System (DAS) defines a communication protocol to exchange annotations on genomic and protein sequences; this standardisation enables clients to retrieve data from a myriad of sources, thus offering centralised access to end-users.
We introduce MyDas, a web server that facilitates the publishing of biological annotations according to the DAS specification. It deals with the common functionality requirements of making data available, while also providing an extension mechanism in order to implement the specifics of data store interaction. MyDas allows the user to define where the required information is located along with its structure, and is then responsible for the communication protocol details.
doi:10.1371/journal.pone.0044180
PMCID: PMC3441562  PMID: 23028496
8.  The IntAct molecular interaction database in 2012 
Nucleic Acids Research  2011;40(D1):D841-D846.
IntAct is an open-source, open data molecular interaction database populated by data either curated from the literature or from direct data depositions. Two levels of curation are now available within the database, with both IMEx-level annotation and less detailed MIMIx-compatible entries currently supported. As from September 2011, IntAct contains approximately 275 000 curated binary interaction evidences from over 5000 publications. The IntAct website has been improved to enhance the search process and in particular the graphical display of the results. New data download formats are also available, which will facilitate the inclusion of IntAct's data in the Semantic Web. IntAct is an active contributor to the IMEx consortium (http://www.imexconsortium.org). IntAct source code and data are freely available at http://www.ebi.ac.uk/intact.
doi:10.1093/nar/gkr1088
PMCID: PMC3245075  PMID: 22121220
9.  Bioinformatics Training Network (BTN): a community resource for bioinformatics trainers 
Briefings in Bioinformatics  2011;13(3):383-389.
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.
doi:10.1093/bib/bbr064
PMCID: PMC3357490  PMID: 22110242
Bioinformatics; training; end users; bioinformatics courses; learning bioinformatics
10.  myKaryoView: A Light-Weight Client for Visualization of Genomic Data 
PLoS ONE  2011;6(10):e26345.
The Distributed Annotation System (DAS) is a protocol for easy sharing and integration of biological annotations. In order to visualize feature annotations in a genomic context a client is required. Here we present myKaryoView, a simple light-weight DAS tool for visualization of genomic annotation. myKaryoView has been specifically configured to help analyse data derived from personal genomics, although it can also be used as a generic genome browser visualization. Several well-known data sources are provided to facilitate comparison of known genes and normal variation regions. The navigation experience is enhanced by simultaneous rendering of different levels of detail across chromosomes. A simple interface is provided to allow searches for any SNP, gene or chromosomal region. User-defined DAS data sources may also be added when querying the system. We demonstrate myKaryoView capabilities for adding user-defined sources with a set of genetic profiles of family-related individuals downloaded directly from 23andMe. myKaryoView is a web tool for visualization of genomic data specifically designed for direct-to-consumer genomic data that uses publicly available data distributed throughout the Internet. It does not require data to be held locally and it is capable of rendering any feature as long as it conforms to DAS specifications. Configuration and addition of sources to myKaryoView can be done through the interface. Here we show a proof of principle of myKaryoView's ability to display personal genomics data with 23andMe genome data sources. The tool is available at: http://mykaryoview.com.
doi:10.1371/journal.pone.0026345
PMCID: PMC3202530  PMID: 22046276
11.  Dasty3, a WEB framework for DAS 
Bioinformatics  2011;27(18):2616-2617.
Motivation: Dasty3 is a highly interactive and extensible Web-based framework. It provides a rich Application Programming Interface upon which it is possible to develop specialized clients capable of retrieving information from DAS sources as well as from data providers not using the DAS protocol. Dasty3 provides significant improvements on previous Web-based frameworks and is implemented using the 1.6 DAS specification.
Availability: Dasty3 is an open-source tool freely available at http://www.ebi.ac.uk/dasty/ under the terms of the GNU General public license. Source and documentation can be found at http://code.google.com/p/dasty/.
Contact: hhe@ebi.ac.uk
doi:10.1093/bioinformatics/btr433
PMCID: PMC3167052  PMID: 21798964
12.  DAS Writeback: A Collaborative Annotation System 
BMC Bioinformatics  2011;12:143.
Background
Centralised resources such as GenBank and UniProt are perfect examples of the major international efforts that have been made to integrate and share biological information. However, additional data that adds value to these resources needs a simple and rapid route to public access. The Distributed Annotation System (DAS) provides an adequate environment to integrate genomic and proteomic information from multiple sources, making this information accessible to the community. DAS offers a way to distribute and access information but it does not provide domain experts with the mechanisms to participate in the curation process of the available biological entities and their annotations.
Results
We designed and developed a Collaborative Annotation System for proteins called DAS Writeback. DAS writeback is a protocol extension of DAS to provide the functionalities of adding, editing and deleting annotations. We implemented this new specification as extensions of both a DAS server and a DAS client. The architecture was designed with the involvement of the DAS community and it was improved after performing usability experiments emulating a real annotation task.
Conclusions
We demonstrate that DAS Writeback is effective, usable and will provide the appropriate environment for the creation and evolution of community protein annotation.
doi:10.1186/1471-2105-12-143
PMCID: PMC3115852  PMID: 21569281
13.  easyDAS: Automatic creation of DAS servers 
BMC Bioinformatics  2011;12:23.
Background
The Distributed Annotation System (DAS) has proven to be a successful way to publish and share biological data. Although there are more than 750 active registered servers from around 50 organizations, setting up a DAS server comprises a fair amount of work, making it difficult for many research groups to share their biological annotations. Given the clear advantage that the generalized sharing of relevant biological data is for the research community it would be desirable to facilitate the sharing process.
Results
Here we present easyDAS, a web-based system enabling anyone to publish biological annotations with just some clicks. The system, available at http://www.ebi.ac.uk/panda-srv/easydas is capable of reading different standard data file formats, process the data and create a new publicly available DAS source in a completely automated way. The created sources are hosted on the EBI systems and can take advantage of its high storage capacity and network connection, freeing the data provider from any network management work. easyDAS is an open source project under the GNU LGPL license.
Conclusions
easyDAS is an automated DAS source creation system which can help many researchers in sharing their biological data, potentially increasing the amount of relevant biological data available to the scientific community.
doi:10.1186/1471-2105-12-23
PMCID: PMC3031199  PMID: 21244646
14.  The Protein Feature Ontology: A Tool for the Unification of Protein Annotations 
Bioinformatics (Oxford, England)  2008;24(23):2767-2772.
The advent of sequencing and structural genomics projects has provided a dramatic boost in the number of protein structures and sequences. Due to the high-throughput nature of these projects, many of the molecules are uncharacterised and their functions unknown. This, in turn, has led to the need for a greater number and diversity of tools and databases providing annotation through transfer based on homology and prediction methods. Though many such tools to annotate protein sequence and structure exist, they are spread throughout the world, often with dedicated individual web pages. This situation does not provide a consensus view of the data and hinders comparison between methods. Integration of these methods is needed. So far this has not been possible since there was no common vocabulary available that could be used as a standard language. A variety of terms could be used to describe any particular feature ranging from different spellings to completely different terms. The Protein Feature Ontology (http://www.ebi.ac.uk/ontology-lookup/browse.do?ontName=BS) is a structured controlled vocabulary for features of a protein sequence or structure. It provides a common language for tools and methods to use, so that integration and comparison of their annotations is possible. The Protein Feature Ontology comprises approximately 100 positional terms (located in a particular region of the sequence), which have been integrated into the Sequence Ontology (SO). 40 non-positional terms which describe general protein properties have also been defined and, in addition, post-translational modifications are described by using an already existing ontology, the Protein Modification Ontology (MOD). The Protein Feature Ontology has been used by the BioSapiens Network of Excellence, a consortium comprising 19 partner sites in 14 European countries generating over 150 distinct annotation types for protein sequences and structures.
doi:10.1093/bioinformatics/btn528
PMCID: PMC2912506  PMID: 18936051
15.  OntoDas – a tool for facilitating the construction of complex queries to the Gene Ontology 
BMC Bioinformatics  2008;9:437.
Background
Ontologies such as the Gene Ontology can enable the construction of complex queries over biological information in a conceptual way, however existing systems to do this are too technical. Within the biological domain there is an increasing need for software that facilitates the flexible retrieval of information. OntoDas aims to fulfil this need by allowing the definition of queries by selecting valid ontology terms.
Results
OntoDas is a web-based tool that uses information visualisation techniques to provide an intuitive, interactive environment for constructing ontology-based queries against the Gene Ontology Database. Both a comprehensive use case and the interface itself were designed in a participatory manner by working with biologists to ensure that the interface matches the way biologists work. OntoDas was further tested with a separate group of biologists and refined based on their suggestions.
Conclusion
OntoDas provides a visual and intuitive means for constructing complex queries against the Gene Ontology. It was designed with the participation of biologists and compares favourably with similar tools. It is available at
doi:10.1186/1471-2105-9-437
PMCID: PMC2579441  PMID: 18925933
16.  Integrating biological data – the Distributed Annotation System 
BMC Bioinformatics  2008;9(Suppl 8):S3.
Background
The Distributed Annotation System (DAS) is a widely adopted protocol for dynamically integrating a wide range of biological data from geographically diverse sources. DAS continues to expand its applicability and evolve in response to new challenges facing integrative bioinformatics.
Results
Here we describe the various infrastructure components of DAS and present a new extended version of the DAS specification. Version 1.53E incorporates several recent developments, including its extension to serve new data types and an ontology for protein features.
Conclusion
Our extensions to the DAS protocol have facilitated the integration of new data types, and our improvements to the existing DAS infrastructure have addressed recent challenges. The steadily increasing numbers of available data sources demonstrates further adoption of the DAS protocol.
doi:10.1186/1471-2105-9-S8-S3
PMCID: PMC2500094  PMID: 18673527

Results 1-16 (16)