@article{Corpas2014, abstract = {BioJS is a community-based standard and repository of functional components to represent biological information on the web. The development of BioJS has been prompted by the growing need for bioinformatics visualisation tools to be easily shared, reused and discovered. Its modular architecture makes it easy for users to find a specific functionality without needing to know how it has been built, while components can be extended or created for implementing new functionality. The BioJS community of developers currently provides a range of functionality that is open access and freely available. A registry has been set up that categorises and provides installation instructions and testing facilities at http://www.ebi.ac.uk/tools/biojs/. The source code for all components is available for ready use at https://github.com/biojs/biojs.}, author = {Corpas, Manuel and Jimenez, Rafael and Carbon, Seth J. and García, Alex and Garcia, Leyla and Goldberg, Tatyana and Gomez, John and Kalderimis, Alexis and Lewis, Suzanna E. and Mulvany, Ian and Pawlik, Aleksandra and Rowland, Francis and Salazar, Gustavo and Schreiber, Fabian and Sillitoe, Ian and Spooner, William H. and Thanki, Anil S. and Villaveces, José M. and Yachdav, Guy and Hermjakob, Henning}, doi = {10.12688/f1000research.3-55.v1}, journal = {F1000Research}, month = {feb}, pages = {55}, title = {BioJS: An open source standard for biological visualisation - its status in 2014}, url = {http://dx.doi.org/10.12688/f1000research.3-55.v1}, volume = {3}, year = {2014} } @article{Corpas2014_2, abstract = {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.}, author = {Corpas, Manuel and Jimenez, Rafael C. and Bongcam-Rudloff, Erik and Budd, Aidan and Brazas, Michelle D. and Fernandes, Pedro L. and Gaeta, Bruno and van Gelder, Celia and Korpelainen, Eija and Lewitter, Fran and McGrath, Annette and MacLean, Daniel and Palagi, Patricia M. and Rother, Kristian and Taylor, Jan and Via, Allegra and Watson, Mick and Schneider, Maria Victoria and Attwood, Teresa K. and Corpas M., Jimenez RC Bongcam-Rudloff E Budd A Brazas MD Fernandes PL Gaeta B van Gelder C Korpelainen E Lewitter F McGrath A MacLean D Palagi PM Rother K Taylor J Via A Watson M Schneider MV Attwood T.-K.}, doi = {10.1093/bioinformatics/btu601}, journal = {Bioinformatics}, month = {sep}, pages = {140-142}, title = {The GOBLET training portal: a global repository of bioinformatics training materials, courses and trainers}, url = {https://academic.oup.com/bioinformatics/article-pdf/31/1/140/6999822/btu601.pdf}, volume = {31}, year = {2014} } @article{Del-Toro2013, abstract = {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).}, author = {Del-Toro, Noemi and Dumousseau, Marine and Orchard, Sandra and Jimenez, Rafael C. and Galeota, Eugenia and Launay, Guillaume and Goll, Johannes and Breuer, Karin and Ono, Keiichiro and Salwinski, Lukasz and Hermjakob, Henning}, doi = {10.1093/nar/gkt392}, journal = {Nucleic Acids Research}, month = {may}, pages = {W601-W606}, title = {A new reference implementation of the PSICQUIC web service}, url = {http://dx.doi.org/10.1093/nar/gkt392}, volume = {41}, year = {2013} } @article{Duarte2015, abstract = {With the increasingly rapid growth of data in life sciences we are witnessing a major transition in the way research is conducted, from hypothesis-driven studies to data-driven simulations of whole systems. Such approaches necessitate the use of large-scale computational resources and e-infrastructures, such as the European Grid Infrastructure (EGI). EGI, one of key the enablers of the digital European Research Area, is a federation of resource providers set up to deliver sustainable, integrated and secure computing services to European researchers and their international partners. Here we aim to provide the state of the art of Grid/Cloud computing in EU research as viewed from within the field of life sciences, focusing on key infrastructures and projects within the life sciences community. Rather than focusing purely on the technical aspects underlying the currently provided solutions, we outline the design aspects and key characteristics that can be identified across major research approaches. Overall, we aim to provide significant insights into the road ahead by establishing ever-strengthening connections between EGI as a whole and the life sciences community.}, author = {Duarte, Afonso Miguel S. and Psomopoulos, Fotis E. and Blanchet, Christophe and Bonvin, Alexandre M. J. J. and Corpas, Manuel and Franc, Alain and Jimenez, Rafael C. and de Lucas, Jesus Marco and Nyrönen, Tommi and Sipos, Gergely and Suhr, Stephanie B.}, doi = {10.3389/fgene.2015.00197}, journal = {Frontiers in Genetics}, month = {jun}, title = {Future opportunities and trends for e-infrastructures and life sciences: going beyond the grid to enable life science data analysis}, url = {http://dx.doi.org/10.3389/fgene.2015.00197}, volume = {6}, year = {2015} } @article{dummy-Author_name2017, author = {dummy-Author_name, and Wolstencroft, Katy and McMurry, Julie A. and Blomberg, Niklas and Burdett, Tony and Mueller, Wolfgang and Conlin, Tom and Conte, Nathalie and Courtot, Melanie and Deck, John and Rc, Jimenez and Dumontier, Michel and Gonzalez-Beltran, Alejandra and Fellows, Donal K. and Gormanns, Philipp and Novère, Nicolas Le and Grethe, Jeffrey and Hastings, Janna and Juty, Navtej and Hermjakob, Henning and Hériché, Jean-Karim and Burdett, Anthony and Ison, Jon C. and Jimenez, Rafael C. and Jupp, Simon and Kunze, John and Laibe, Camille and Ja, McMurry and Morris, Chris and Malone, James Robert and Le Novere, Nicolas and Muilu, Juha and Martin, Maria-Jesus and Müller, Wolfgang and Rocca-Serra, Philippe and Sansone, Susanna-Assunta and Sariyar, Murat and Snoep, Jacky L. and Stanford, Natalie J. and Soiland-Reyes, Stian and Swainston, Neil and Burdett, T. and Washington, Nicole and Williams, Alan R. and Heriche, Jean-Karim and Wimalaratne, Sarala M. and Winfree, Lilly M. and Dk, Fellows and McEntyre, Jo and Jk, Hériché and Mungall, Christopher J. and Goble, Carole and Jc, Ison and Haendel, Melissa A. and Parkinson, Helen}, doi = {10.1371/journal.pbio.2001414}, journal = {PLoS Biology}, month = {mar}, pages = {e2001414}, title = {Identifiers for the 21st century: How to design, provision, and reuse persistent identifiers to maximize utility and impact of life science data}, url = {https://doi.org/10.1371/journal.pbio.2001414}, volume = {15}, year = {2017} } @article{Garcia2020, author = {Garcia, Leyla and Antezana, Erick and Garcia, Alexander and Bolton, Evan and Jimenez, Rafael and Prins, Pjotr and Banda, Juan M. and Katayama, Toshiaki}, doi = {10.1371/journal.pcbi.1007808}, journal = {PLoS Computational Biology}, month = {may}, pages = {e1007808}, title = {Ten simple rules to run a successful BioHackathon}, url = {https://doi.org/10.1371/journal.pcbi.1007808}, volume = {16}, year = {2020} } @article{Gomez2014, abstract = {Summary: Sequences are probably the most common piece of information in sites providing biological data resources, particularly those related to genes and proteins. Multiple visual representations of the same sequence can be found across those sites. This can lead to an inconsistency compromising both the user experience and usability while working with graphical representations of a sequence. Furthermore, the code of the visualisation module is commonly embedded and merged with the rest of the application, making it difficult to reuse it in other applications. In this paper, we present a BioJS component for visualising sequences with a set of options supporting a flexible configuration of the visual representation, such as formats, colours, annotations, and columns, among others. This component aims to facilitate a common representation across different sites, making it easier for end users to move from one site to another.Availability: http://www.ebi.ac.uk/Tools/biojs; http://dx.doi.org/10.5281/zenodo.8299}, author = {Gomez, John and Jimenez, Rafael}, doi = {10.12688/f1000research.3-52.v1}, journal = {F1000Research}, month = {feb}, pages = {52}, title = {Sequence, a BioJS component for visualising sequences}, url = {http://dx.doi.org/10.12688/f1000research.3-52.v1}, volume = {3}, year = {2014} } @article{Gómez2013, abstract = {Summary: BioJS is an open-source project whose main objective is the visualization of biological data in JavaScript. BioJS provides an easy-to-use consistent framework for bioinformatics application programmers. It follows a community-driven standard specification that includes a collection of components purposely designed to require a very simple configuration and installation. In addition to the programming framework, BioJS provides a centralized repository of components available for reutilization by the bioinformatics community.}, author = {Gómez, John and Gomez, J. and García, Leyla J. and Salazar, Gustavo A. and Villaveces, Jose and Gore, Swanand and García, Alexander and Martín, Maria J. and Launay, Guillaume and Alcántara, Rafael and del-Toro, Noemi and Del Toro Ayllón, Noemi and Dumousseau, Marine and Orchard, Sandra and Velankar, Sameer and Hermjakob, Henning and Zong, Chenggong and Ping, Peipei and Corpas, Manuel and Jiménez, Rafael C.}, doi = {10.1093/bioinformatics/btt100}, journal = {Bioinformatics}, month = {feb}, pages = {1103-1104}, title = {BioJS: an open source JavaScript framework for biological data visualization}, url = {https://academic.oup.com/bioinformatics/article-pdf/29/8/1103/633776/btt100.pdf}, volume = {29}, year = {2013} } @article{Ison2015, abstract = {Life sciences are yielding huge data sets that underpin scientific discoveries fundamental to improvement in human health, agriculture and the environment. In support of these discoveries, a plethora of databases and tools are deployed, in technically complex and diverse implementations, across a spectrum of scientific disciplines. The corpus of documentation of these resources is fragmented across the Web, with much redundancy, and has lacked a common standard of information. The outcome is that scientists must often struggle to find, understand, compare and use the best resources for the task at hand. Here we present a community-driven curation effort, supported by ELIXIR––the European infrastructure for biological information––that aspires to a comprehensive and consistent registry of information about bioinformatics resources. The sustainable upkeep of this Tools and Data Services Registry is assured by a curation effort driven by and tailored to local needs, and shared amongst a network of engaged partners. As of November 2015, the registry includes 1785 resources, with depositions from 126 individual registrations including 52 institutional providers and 74 individuals. With community support, the registry can become a standard for dissemination of information about bioinformatics resources: we welcome everyone to join us in this common endeavour. The registry is freely available at https://bio.tools.}, author = {Ison, Jon and Rapacki, Kristoffer and Ménager, Hervé and Kalaš, Matúš and Rydza, Emil and Vedova, Gianluca Della and Chmura, Piotr and Emery, Laura and Anthon, Christian and Gasteiger, Elisabeth and Beard, Niall and Gatter, Thomas and Goldberg, Tatyana and Berka, Karel and Grosjean, Marie and Bolser, Dan and Grüning, Björn and Helmer-Citterich, Manuela and Booth, Tim and Ienasescu, Hans and Bretaudeau, Anthony and Ioannidis, Vassilios and Jespersen, Martin Closter and Brezovsky, Jan and Jimenez, Rafael and Casadio, Rita and Juty, Nick and Juvan, Peter and Cesareni, Gianni and Koch, Maximilian and Coppens, Frederik and Laibe, Camille and Cornell, Michael and Li, Jing-Woei and Cuccuru, Gianmauro and Licata, Luana and Davidsen, Kristian and Mareuil, Fabien and Mičetić, Ivan and Dogan, Tunca and Friborg, Rune Møllegaard and Doppelt-Azeroual, Olivia and Moretti, Sebastien and Morris, Chris and Möller, Steffen and Nenadic, Aleksandra and Peterson, Hedi and Profiti, Giuseppe and Rice, Peter and Romano, Paolo and Roncaglia, Paola and Saidi, Rabie and Schafferhans, Andrea and Schwämmle, Veit and Smith, Callum and Sperotto, Maria Maddalena and Stockinger, Heinz and Vařeková, Radka Svobodová and Tosatto, Silvio Ce E. and de la Torre, Victor and Uva, Paolo and Via, Allegra and Yachdav, Guy and Zambelli, Federico and Vriend, Gert and Rost, Burkhard and Parkinson, Helen and Løngreen, Peter and Della Vedova, Gianluca and Brunak, Søren and Authors, 69}, doi = {10.1093/nar/gkv1116}, journal = {Nucleic Acids Research}, month = {nov}, pages = {D38-D47}, title = {Tools and data services registry: a community effort to document bioinformatics resources}, url = {https://doi.org/10.1093/nar/gkv1116}, volume = {44}, year = {2015} } @article{Jiménez2017, abstract = {Scientific research relies on computer software, yet software is not always developed following practices that ensure its quality and sustainability. This manuscript does not aim to propose new software development best practices, but rather to provide simple recommendations that encourage the adoption of existing best practices. Software development best practices promote better quality software, and better quality software improves the reproducibility and reusability of research. These recommendations are designed around Open Source values, and provide practical suggestions that contribute to making research software and its source code more discoverable, reusable and transparent. This manuscript is aimed at developers, but also at organisations, projects, journals and funders that can increase the quality and sustainability of research software by encouraging the adoption of these recommendations.}, author = {Jiménez, Rafael C. and Kuzak, Mateusz and Alhamdoosh, Monther and Barker, Michelle and Batut, Bérénice and Borg, Mikael and Capella-Gutierrez, Salvador and Chue Hong, Neil and Cook, Martin and Corpas, Manuel and Flannery, Madison and Garcia, Leyla and Gelpí, Josep L.-L. and Gladman, Simon and Goble, Carole and González Ferreiro, Montserrat and Gonzalez-Beltran, Alejandra and Griffin, Philippa C. and Grüning, Björn and Hagberg, Jonas and Holub, Petr and Hooft, Rob and Ison, Jon and Katz, Daniel S. and Leskošek, Brane and López Gómez, Federico and Oliveira, Luis J. and Mellor, David and Mosbergen, Rowland and Mulder, Nicola and Perez-Riverol, Yasset and Pergl, Robert and Pichler, Horst and Pope, Bernard and Sanz, Ferran and Schneider, Maria V. and Stodden, Victoria and Suchecki, Radosław and Svobodová Vařeková, Radka and Talvik, Harry-Anton and Todorov, Ilian and Treloar, Andrew and Tyagi, Sonika and van Gompel, Maarten and Vaughan, Daniel and Via, Allegra and Wang, Xiaochuan and Watson-Haigh, Nathan S. and Crouch, Steve}, doi = {10.12688/f1000research.11407.1}, journal = {F1000Research}, month = {jun}, pages = {876}, title = {Four simple recommendations to encourage best practices in research software}, url = {https://f1000research.com/articles/6-876/v1/pdf}, volume = {6}, year = {2017} } @article{Lapatas2015, abstract = {Data sharing, integration and annotation are essential to ensure the reproducibility of the analysis and interpretation of the experimental findings. Often these activities are perceived as a role that bioinformaticians and computer scientists have to take with no or little input from the experimental biologist. On the contrary, biological researchers, being the producers and often the end users of such data, have a big role in enabling biological data integration. The quality and usefulness of data integration depend on the existence and adoption of standards, shared formats, and mechanisms that are suitable for biological researchers to submit and annotate the data, so it can be easily searchable, conveniently linked and consequently used for further biological analysis and discovery. Here, we provide background on what is data integration from a computational science point of view, how it has been applied to biological research, which key aspects contributed to its success and future directions.}, author = {Lapatas, Vasileios and Stefanidakis, Michalis and Jimenez, Rafael C. and Via, Allegra and Schneider, Maria Victoria}, doi = {10.1186/s40709-015-0032-5}, journal = {Journal of Biological Research-Thessaloniki}, month = {sep}, title = {Data integration in biological research: An overview}, url = {http://dx.doi.org/10.1186/s40709-015-0032-5}, volume = {22}, year = {2015} } @article{Orchard2013, abstract = {IntAct (freely available at http://www.ebi.ac.uk/intact) is an open-source, open data molecular interaction database populated by data either curated from the literature or from direct data depositions. IntAct has developed a sophisticated web-based curation tool, capable of supporting both IMEx- and MIMIx-level curation. This tool is now utilized by multiple additional curation teams, all of whom annotate data directly into the IntAct database. Members of the IntAct team supply appropriate levels of training, perform quality control on entries and take responsibility for long-term data maintenance. Recently, the MINT and IntAct databases decided to merge their separate efforts to make optimal use of limited developer resources and maximize the curation output. All data manually curated by the MINT curators have been moved into the IntAct database at EMBL-EBI and are merged with the existing IntAct dataset. Both IntAct and MINT are active contributors to the IMEx consortium (http://www.imexconsortium.org).}, author = {Orchard, Sandra and Ammari, Mais and Aranda, Bruno and Breuza, Lionel and Briganti, Leonardo and Broackes-Carter, Fiona and Campbell, Nancy H. and Chavali, Gayatri and Chen, Carol and Del-Toro, Noemi and Duesbury, Margaret and Dumousseau, Marine and Galeota, Eugenia and Hinz, Ursula and Iannuccelli, Marta and Jagannathan, Sruthi and Jimenez, Rafael and Khadake, Jyoti and Lagreid, Astrid and Licata, Luana and Lovering, Ruth C. and Meldal, Birgit and Melidoni, Anna N. and Milagros, Mila and Peluso, Daniele and Perfetto, Livia and Porras, Pablo and Raghunath, Arathi and Ricard-Blum, Sylvie and Roechert, Bernd and Stutz, Andre and Tognolli, Michael and van Roey, Kim and Cesareni, Gianni and Hermjakob, Henning}, doi = {10.1093/nar/gkt1115}, journal = {Nucleic Acids Research}, month = {nov}, pages = {D358-D363}, title = {The MIntAct project—IntAct as a common curation platform for 11 molecular interaction databases}, url = {https://doi.org/10.1093/nar/gkt1115}, volume = {42}, year = {2013} } @article{Rc2013, abstract = {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.}, author = {Rc, Jimenez and Jp, Albar and Mc, Blatter and Md, Brazas and Jimenez, Rafael C. and Rivas, J. De Las and Ma, van Driel and Albar, Juan P. and Bhak, Jong and Mj, Dunn and Pl, Fernandes and Blatter, Marie-Claude and Blicher, Thomas and P., David and Brazas, Michelle D. and Brooksbank, Cath and van Driel, Marc A. and Budd, Aidan and van Gelder, Celia W. G. and De Las Rivas, Javier and Dunn, Michael J. and Judge, David P. and Dreyer, Jacqueline and Fernandes, Pedro L. and Kahlem, Pascal and Jm, Villaveces and Korpelainen, Eija and Hermjakob, Henning and Kraus, Hans-Joachim and Ioannidis, Vassilios and Loveland, Jane and Mayer, Christine and Schneider, Reinhard and McDowall, Jennifer and Moran, Federico and Mv, Schneider and Mulder, Nicola and Tk, Attwood and Nyronen, Tommi and Rother, Kristian and Salazar, Gustavo A. and Driel, M. A. van and Via, Allegra and Villaveces, Jose M. and Cw, van Gelder and Gelder, C. W. G. van and Yu, Ping and Dp, Judge and Schneider, Maria V. and D. P., Judge and Hj, Kraus and Ga, Salazar and Attwood, Teresa K. and Corpas, Manuel}, doi = {10.1093/bioinformatics/btt306}, journal = {Bioinformatics}, month = {jun}, pages = {1919-1921}, title = {iAnn: an event sharing platform for the life sciences}, url = {https://academic.oup.com/bioinformatics/article-pdf/29/15/1919/736531/btt306.pdf}, volume = {29}, year = {2013} } @misc{Tenenbaum2018, author = {Tenenbaum, Jessica and Sansone, Susanna-Assunta and Schriml, Lynn and Rustici, Gabriella and Schurer, Stephan and Sharples, Kathryn and Rocca-Serra, Philippe and Soares e. Silva, Marina and Stanford, Natalie J. and Subirats-Coll, Inmaculada and Swedlow, Jason and Tong, Weida and McQuilton, Peter and Wilkinson, Mark and Wise, John and Hodson, Simon and Gonzalez-Beltran, Alejandra and Lawrence, Rebecca and Thurston, Milo and Khodiyar, Varsha and Axton, J. Myles and Ball, Michael and Izzo, Massimiliano and Besson, Sebastien and Bloom, Theodora and Bonazzi, Vivien and Lister, Allyson and Jimenez, Rafael and Carr, David and Chan, Wei Mun and Chung, Caty and Clement-Stoneham, Geraldine and Cousijn, Helena and Dayalan, Saravanan and Batista, Dominique and Dumontier, Michel and Dzale Yeumo, Esther and Edmunds, Scott and Everitt, Nicholas and Granell, Ramon and Yilmaz, Pelin and Fripp, Dom and Goble, Carole and Golebiewski, Martin and Hall, Neil and Adekale, Melanie and Hanisch, Robert and Hucka, Michael and Huerta, Michael and Dauga, Delphine and Kenall, Amye and Kiley, Robert and Klenk, Juergen and Koureas, Dimitrios and Larkin, Jennie and Ganley, Emma and Lemberger, Thomas and Lynch, Nick and Ma'ayan, Avi and MacCallum, Catriona and Mons, Barend and Moore, Josh and Muller, Wolfgang and Murray, Hollydawn and Nobusada, Tomoe and Noesgaard, Daniel and Paxton-Boyd, Jennifer and Orchard, Sandra and Rn, Lawrence}, month = {jan}, title = {FAIRsharing, a cohesive community approach to the growth in standards, repositories and policies}, year = {2018} } @article{van Rijswijk2017, abstract = {Metabolomics, the youngest of the major omics technologies, is supported by an active community of researchers and infrastructure developers across Europe. To coordinate and focus efforts around infrastructure building for metabolomics within Europe, a workshop on the “Future of metabolomics in ELIXIR” was organised at Frankfurt Airport in Germany. This one-day strategic workshop involved representatives of ELIXIR Nodes, members of the PhenoMeNal consortium developing an e-infrastructure that supports workflow-based metabolomics analysis pipelines, and experts from the international metabolomics community. The workshop established metabolite identification as the critical area, where a maximal impact of computational metabolomics and data management on other fields could be achieved. In particular, the existing four ELIXIR Use Cases, where the metabolomics community - both industry and academia - would benefit most, and which could be exhaustively mapped onto the current five ELIXIR Platforms were discussed. This opinion article is a call for support for a new ELIXIR metabolomics Use Case, which aligns with and complements the existing and planned ELIXIR Platforms and Use Cases.}, author = {van Rijswijk, Merlijn and Beirnaert, Charlie and Caron, Christophe and Cascante, Marta and Dominguez, Victoria and Dunn, Warwick B. and Ebbels, Timothy M. D. and Giacomoni, Franck and Gonzalez-Beltran, Alejandra and Hankemeier, Thomas and Haug, Kenneth and Izquierdo-Garcia, Jose L. and Jimenez, Rafael C. and Jourdan, Fabien and Kale, Namrata and Klapa, Maria I. and Kohlbacher, Oliver and Koort, Kairi and Kultima, Kim and Le Corguillé, Gildas and Moreno, Pablo and Moschonas, Nicholas K. and Neumann, Steffen and O’Donovan, Claire and Reczko, Martin and Rocca-Serra, Philippe and Rosato, Antonio and Salek, Reza M. and Sansone, Susanna-Assunta and Satagopam, Venkata and Schober, Daniel and Shimmo, Ruth and Spicer, Rachel A. and Spjuth, Ola and Thévenot, Etienne A. and Viant, Mark R. and Weber, Ralf J. M. and Willighagen, Egon L. and Zanetti, Gianluigi and Steinbeck, Christoph}, doi = {10.12688/f1000research.12342.2}, journal = {F1000Research}, month = {oct}, pages = {1649}, title = {The future of metabolomics in ELIXIR}, url = {https://f1000research.com/articles/6-1649/v2/pdf}, volume = {6}, year = {2017} } @article{Via2013, abstract = {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.}, author = {Via, Allegra and Blicher, Thomas and Bongcam-Rudloff, Erik and Brazas, Michelle D. and Md, Brazas and Brooksbank, Cath and Budd, Aidan and De Las Rivas, Javier and Rivas, J. De Las and Dreyer, Jacqueline and Pl, Fernandes and Fernandes, Pedro L. and van Gelder, Celia and Gelder, C. W. van and Jacob, Joachim and Rc, Jimenez and Jimenez, Rafael C. and Loveland, Jane and Moran, Federico and Mulder, Nicola and Nyrönen, Tommi and Rother, Kristian and Mv, Schneider and Schneider, Maria Victoria and Attwood, Teresa K. and Tk, Attwood}, doi = {10.1093/bib/bbt043}, journal = {Briefings in Bioinformatics}, month = {jun}, pages = {528-537}, title = {Best practices in bioinformatics training for life scientists}, url = {https://academic.oup.com/bib/article-pdf/14/5/528/583675/bbt043.pdf}, volume = {14}, year = {2013} } @article{Villaveces2014, abstract = {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.}, author = {Villaveces, Jose M. and Jimenez, Rafael C. and Habermann, Bianca H.}, doi = {10.12688/f1000research.3-43.v1}, journal = {F1000Research}, month = {feb}, pages = {43}, title = {KEGGViewer, a BioJS component to visualize KEGG Pathways}, url = {http://dx.doi.org/10.12688/f1000research.3-43.v1}, volume = {3}, year = {2014} } @article{Villaveces2014_2, abstract = {Summary: Protein interaction networks have become an essential tool in large-scale data analysis, integration, and the visualization of high-throughput data in the context of complex cellular networks. Many individual databases are available that provide information on binary interactions of proteins and small molecules. Community efforts such as PSICQUIC aim to unify and standardize information emanating from these public databases. Here we introduce PsicquicGraph, an open-source, web-based visualization component for molecular interactions from PSIQUIC services. Availability: PsicquicGraph is freely available at the BioJS Registry for download and enhancement. Instructions on how to use the tool are available here http://goo.gl/kDaIgZ and the source code can be found at http://github.com/biojs/biojs and DOI:10.5281/zenodo.7709.}, author = {Villaveces, Jose M. and Jimenez, Rafael C. and Habermann, Bianca H.}, doi = {10.12688/f1000research.3-44.v1}, journal = {F1000Research}, month = {feb}, pages = {44}, title = {PsicquicGraph, a BioJS component to visualize molecular interactions from PSICQUIC servers}, url = {http://dx.doi.org/10.12688/f1000research.3-44.v1}, volume = {3}, year = {2014} } @article{Wimalaratne2017, abstract = {AbstractMost biomedical data repositories issue locally-unique accessions numbers, but do not provide globally unique, machine-resolvable, persistent identifiers for their datasets, as required by publishers wishing to implement data citation in accordance with widely accepted principles. Local accessions may however be prefixed with a namespace identifier, providing global uniqueness. Such “compact identifiers” have been widely used in biomedical informatics to support global resource identification with local identifier assignment. We report here on our project to provide robust support for machine-resolvable, persistent compact identifiers in biomedical data citation, by harmonizing the Identifiers.org and N2T.net (Name-To-Thing) meta-resolvers and extending their capabilities. Identifiers.org services hosted at the European Molecular Biology Laboratory - European Bioinformatics Institute (EMBL-EBI), and N2T.net services hosted at the California Digital Library (CDL), can now resolve any given identifier from over 600 source databases to its original source on the Web, using a common registry of prefix-based redirection rules. We believe these services will be of significant help to publishers and others implementing persistent, machine-resolvable citation of research data.}, author = {Wimalaratne, Sarala M. and Juty, Nick and Kunze, John and Janée, Greg and McMurry, Julie A. and Beard, Niall and Jimenez, Rafael and Grethe, Jeffrey S. and Hermjakob, Henning and Martone, Maryann E. and Clark, Tim}, doi = {10.1038/sdata.2018.29}, journal = {Scientific Data}, month = {jan}, title = {Uniform Resolution of Compact Identifiers for Biomedical Data}, url = {https://www.nature.com/articles/sdata201829.pdf}, volume = {5}, year = {2017} } @article{Zong2013, abstract = { Rationale : Omics sciences enable a systems-level perspective in characterizing cardiovascular biology. Integration of diverse proteomics data via a computational strategy will catalyze the assembly of contextualized knowledge, foster discoveries through multidisciplinary investigations, and minimize unnecessary redundancy in research efforts. Objective : The goal of this project is to develop a consolidated cardiac proteome knowledgebase with novel bioinformatics pipeline and Web portals, thereby serving as a new resource to advance cardiovascular biology and medicine. Methods and Results : We created Cardiac Organellar Protein Atlas Knowledgebase (COPaKB; www.HeartProteome.org ), a centralized platform of high-quality cardiac proteomic data, bioinformatics tools, and relevant cardiovascular phenotypes. Currently, COPaKB features 8 organellar modules, comprising 4203 LC-MS/MS experiments from human, mouse, drosophila, and Caenorhabditis elegans , as well as expression images of 10 924 proteins in human myocardium. In addition, the Java-coded bioinformatics tools provided by COPaKB enable cardiovascular investigators in all disciplines to retrieve and analyze pertinent organellar protein properties of interest. Conclusions : COPaKB provides an innovative and interactive resource that connects research interests with the new biological discoveries in protein sciences. With an array of intuitive tools in this unified Web server, nonproteomics investigators can conveniently collaborate with proteomics specialists to dissect the molecular signatures of cardiovascular phenotypes. }, author = {Zong, Nobel C. and Li, Haomin and Li, Hua and Lam, Maggie P. Y. and Kim, Christina S. and Jimenez, Rafael C. and Kim, Allen K. and Deng, Ning and Zelaya, Ivette and Liem, David and Choi, Jeong Ho and Meyer, David and Odeberg, Jacob and Lu, Hao-Jie and Fang, Caiyun and Xu, Tao and Weiss, James and Duan, Huilong and Uhlen, Mathias and Yates, John R. and Apweiler, Rolf and Ge, Junbo and Hermjakob, Henning and Ping, Peipei}, doi = {10.1161/circresaha.113.301151}, journal = {Circulation Research}, month = {aug}, pages = {1043-1053}, title = {Integration of Cardiac Proteome Biology and Medicine by a Specialized Knowledgebase}, url = {http://www.ncbi.nlm.nih.gov/pubmed/23965338}, volume = {113}, year = {2013} }