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11 Publications visible to you, out of a total of 11
COVID19 Disease Map, a computational knowledge repository of virus-host interaction mechanisms.

Abstract (Expand)

We need to effectively combine the knowledge from surging literature with complex datasets to propose mechanistic models of SARS-CoV-2 infection, improving data interpretation and predicting key targets … of intervention. Here, we describe a large-scale community effort to build an open access, interoperable and computable repository of COVID-19 molecular mechanisms. The COVID-19 Disease Map (C19DMap) is a graphical, interactive representation of disease-relevant molecular mechanisms linking many knowledge sources. Notably, it is a computational resource for graph-based analyses and disease modelling. To this end, we established a framework of tools, platforms and guidelines necessary for a multifaceted community of biocurators, domain experts, bioinformaticians and computational biologists. The diagrams of the C19DMap, curated from the literature, are integrated with relevant interaction and text mining databases. We demonstrate the application of network analysis and modelling approaches by concrete examples to highlight new testable hypotheses. This framework helps to find signatures of SARS-CoV-2 predisposition, treatment response or prioritisation of drug candidates. Such an approach may help deal with new waves of COVID-19 or similar pandemics in the long-term perspective.

Authors: M. Ostaszewski, A. Niarakis, A. Mazein, I. Kuperstein, R. Phair, A. Orta-Resendiz, V. Singh, S. S. Aghamiri, M. L. Acencio, E. Glaab, A. Ruepp, G. Fobo, C. Montrone, B. Brauner, G. Frishman, L. C. Monraz Gomez, J. Somers, M. Hoch, S. Kumar Gupta, J. Scheel, H. Borlinghaus, T. Czauderna, F. Schreiber, A. Montagud, M. Ponce de Leon, A. Funahashi, Y. Hiki, N. Hiroi, T. G. Yamada, A. Drager, A. Renz, M. Naveez, Z. Bocskei, F. Messina, D. Bornigen, L. Fergusson, M. Conti, M. Rameil, V. Nakonecnij, J. Vanhoefer, L. Schmiester, M. Wang, E. E. Ackerman, J. E. Shoemaker, J. Zucker, K. Oxford, J. Teuton, E. Kocakaya, G. Y. Summak, K. Hanspers, M. Kutmon, S. Coort, L. Eijssen, F. Ehrhart, D. A. B. Rex, D. Slenter, M. Martens, N. Pham, R. Haw, B. Jassal, L. Matthews, M. Orlic-Milacic, A. Senff Ribeiro, K. Rothfels, V. Shamovsky, R. Stephan, C. Sevilla, T. Varusai, J. M. Ravel, R. Fraser, V. Ortseifen, S. Marchesi, P. Gawron, E. Smula, L. Heirendt, V. Satagopam, G. Wu, A. Riutta, M. Golebiewski, S. Owen, C. Goble, X. Hu, R. W. Overall, D. Maier, A. Bauch, B. M. Gyori, J. A. Bachman, C. Vega, V. Groues, M. Vazquez, P. Porras, L. Licata, M. Iannuccelli, F. Sacco, A. Nesterova, A. Yuryev, A. de Waard, D. Turei, A. Luna, O. Babur, S. Soliman, A. Valdeolivas, M. Esteban-Medina, M. Pena-Chilet, K. Rian, T. Helikar, B. L. Puniya, D. Modos, A. Treveil, M. Olbei, B. De Meulder, S. Ballereau, A. Dugourd, A. Naldi, V. Noel, L. Calzone, C. Sander, E. Demir, T. Korcsmaros, T. C. Freeman, F. Auge, J. S. Beckmann, J. Hasenauer, O. Wolkenhauer, E. L. Wilighagen, A. R. Pico, C. T. Evelo, M. E. Gillespie, L. D. Stein, H. Hermjakob, P. D'Eustachio, J. Saez-Rodriguez, J. Dopazo, A. Valencia, H. Kitano, E. Barillot, C. Auffray, R. Balling, R. Schneider

Date Published: 19th Oct 2021

Publication Type: Journal

COVID19 Disease Map, a computational knowledge repository of virus–host interaction mechanisms

Abstract

Not specified

Authors: Marek Ostaszewski, Anna Niarakis, Alexander Mazein, Inna Kuperstein, Robert Phair, Aurelio Orta‐Resendiz, Vidisha Singh, Sara Sadat Aghamiri, Marcio Luis Acencio, Enrico Glaab, Andreas Ruepp, Gisela Fobo, Corinna Montrone, Barbara Brauner, Goar Frishman, Luis Cristóbal Monraz Gómez, Julia Somers, Matti Hoch, Shailendra Kumar Gupta, Julia Scheel, Hanna Borlinghaus, Tobias Czauderna, Falk Schreiber, Arnau Montagud, Miguel Ponce de Leon, Akira Funahashi, Yusuke Hiki, Noriko Hiroi, Takahiro G Yamada, Andreas Dräger, Alina Renz, Muhammad Naveez, Zsolt Bocskei, Francesco Messina, Daniela Börnigen, Liam Fergusson, Marta Conti, Marius Rameil, Vanessa Nakonecnij, Jakob Vanhoefer, Leonard Schmiester, Muying Wang, Emily E Ackerman, Jason E Shoemaker, Jeremy Zucker, Kristie Oxford, Jeremy Teuton, Ebru Kocakaya, Gökçe Yağmur Summak, Kristina Hanspers, Martina Kutmon, Susan Coort, Lars Eijssen, Friederike Ehrhart, Devasahayam Arokia Balaya Rex, Denise Slenter, Marvin Martens, Nhung Pham, Robin Haw, Bijay Jassal, Lisa Matthews, Marija Orlic‐Milacic, Andrea Senff Ribeiro, Karen Rothfels, Veronica Shamovsky, Ralf Stephan, Cristoffer Sevilla, Thawfeek Varusai, Jean‐Marie Ravel, Rupsha Fraser, Vera Ortseifen, Silvia Marchesi, Piotr Gawron, Ewa Smula, Laurent Heirendt, Venkata Satagopam, Guanming Wu, Anders Riutta, Martin Golebiewski, Stuart Owen, Carole Goble, Xiaoming Hu, Rupert W Overall, Dieter Maier, Angela Bauch, Benjamin M Gyori, John A Bachman, Carlos Vega, Valentin Grouès, Miguel Vazquez, Pablo Porras, Luana Licata, Marta Iannuccelli, Francesca Sacco, Anastasia Nesterova, Anton Yuryev, Anita de Waard, Denes Turei, Augustin Luna, Ozgun Babur, Sylvain Soliman, Alberto Valdeolivas, Marina Esteban‐Medina, Maria Peña‐Chilet, Kinza Rian, Tomáš Helikar, Bhanwar Lal Puniya, Dezso Modos, Agatha Treveil, Marton Olbei, Bertrand De Meulder, Stephane Ballereau, Aurélien Dugourd, Aurélien Naldi, Vincent Noël, Laurence Calzone, Chris Sander, Emek Demir, Tamas Korcsmaros, Tom C Freeman, Franck Augé, Jacques S Beckmann, Jan Hasenauer, Olaf Wolkenhauer, Egon L Wilighagen, Alexander R Pico, Chris T Evelo, Marc E Gillespie, Lincoln D Stein, Henning Hermjakob, Peter D'Eustachio, Julio Saez‐Rodriguez, Joaquin Dopazo, Alfonso Valencia, Hiroaki Kitano, Emmanuel Barillot, Charles Auffray, Rudi Balling, Reinhard Schneider

Date Published: 1st Oct 2021

Publication Type: Journal

Data Management in Computational Systems Biology: Exploring Standards, Tools, Databases, and Packaging Best Practices.

Abstract (Expand)

Computational systems biology involves integrating heterogeneous datasets in order to generate models. These models can assist with understanding and prediction of biological phenomena. Generating … datasets and integrating them into models involves a wide range of scientific expertise. As a result these datasets are often collected by one set of researchers, and exchanged with others researchers for constructing the models. For this process to run smoothly the data and models must be FAIR-findable, accessible, interoperable, and reusable. In order for data and models to be FAIR they must be structured in consistent and predictable ways, and described sufficiently for other researchers to understand them. Furthermore, these data and models must be shared with other researchers, with appropriately controlled sharing permissions, before and after publication. In this chapter we explore the different data and model standards that assist with structuring, describing, and sharing. We also highlight the popular standards and sharing databases within computational systems biology.

Authors: N. J. Stanford, M. Scharm, P. D. Dobson, M. Golebiewski, M. Hucka, V. B. Kothamachu, D. Nickerson, S. Owen, J. Pahle, U. Wittig, D. Waltemath, C. Goble, P. Mendes, J. Snoep

Date Published: 12th Oct 2019

Publication Type: Journal

FAIRDOMHub: a repository and collaboration environment for sharing systems biology research.

Abstract (Expand)

The FAIRDOMHub is a repository for publishing FAIR (Findable, Accessible, Interoperable and Reusable) Data, Operating procedures and Models (https://fairdomhub.org/) for the Systems Biology community. … It is a web-accessible repository for storing and sharing systems biology research assets. It enables researchers to organize, share and publish data, models and protocols, interlink them in the context of the systems biology investigations that produced them, and to interrogate them via API interfaces. By using the FAIRDOMHub, researchers can achieve more effective exchange with geographically distributed collaborators during projects, ensure results are sustained and preserved and generate reproducible publications that adhere to the FAIR guiding principles of data stewardship.

Authors: K. Wolstencroft, O. Krebs, J. L. Snoep, N. J. Stanford, F. Bacall, M. Golebiewski, R. Kuzyakiv, Q. Nguyen, S. Owen, S. Soiland-Reyes, J. Straszewski, D. D. van Niekerk, A. R. Williams, L. Malmstrom, B. Rinn, W. Muller, C. Goble

Date Published: 4th Jan 2017

Publication Type: Journal

FAIRDOMHub: a repository and collaboration environment for sharing systems biology research.

Abstract (Expand)

The FAIRDOMHub is a repository for publishing FAIR (Findable, Accessible, Interoperable and Reusable) Data, Operating procedures and Models (https://fairdomhub.org/) for the Systems Biology community. … It is a web-accessible repository for storing and sharing systems biology research assets. It enables researchers to organize, share and publish data, models and protocols, interlink them in the context of the systems biology investigations that produced them, and to interrogate them via API interfaces. By using the FAIRDOMHub, researchers can achieve more effective exchange with geographically distributed collaborators during projects, ensure results are sustained and preserved and generate reproducible publications that adhere to the FAIR guiding principles of data stewardship.

Authors: K. Wolstencroft, O. Krebs, J. L. Snoep, N. J. Stanford, F. Bacall, M. Golebiewski, R. Kuzyakiv, Q. Nguyen, S. Owen, S. Soiland-Reyes, J. Straszewski, D. D. van Niekerk, A. R. Williams, L. Malmstrom, B. Rinn, W. Muller, C. Goble

Date Published: 4th Jan 2017

Publication Type: Journal

Stealthy annotation of experimental biology by spreadsheets

Abstract (Expand)

The increase in volume and complexity of biological data has led to increased requirements to reuse that data. Consistent and accurate metadata is essential for this task, creating new challenges in … semantic data annotation and in the constriction of terminologies and ontologies used for annotation. The BioSharing community are developing standards and terminologies for annotation, which have been adopted across bioinformatics, but the real challenge is to make these standards accessible to laboratory scientists. Widespread adoption requires the provision of tools to assist scientists whilst reducing the complexities of working with semantics. This paper describes unobtrusive ‘stealthy’ methods for collecting standards compliant, semantically annotated data and for contributing to ontologies used for those annotations. Spreadsheets are ubiquitous in laboratory data management. Our spreadsheet-based RightField tool enables scientists to structure information and select ontology terms for annotation within spreadsheets, producing high quality, consistent data without changing common working practices. Furthermore, our Populous spreadsheet tool proves effective for gathering domain knowledge in the form of Web Ontology Language (OWL) ontologies. Such a corpus of structured and semantically enriched knowledge can be extracted in Resource Description Framework (RDF), providing further means for searching across the content and contributing to Open Linked Data (http://linkeddata.org/)

Authors: , , Matthew Horridge, Simon Jupp, , , , , Robert Stevens,

Date Published: 1st Feb 2013

Publication Type: Journal

Semantic Data and Models Sharing in Systems Biology: The Just Enough Results Model and the SEEK Platform

Abstract (Expand)

Research in Systems Biology involves integrating data and knowledge about the dynamic processes in biological systems in order to understand and model them. Semantic web technologies should be ideal … for exploring the complex networks of genes, proteins and metabolites that interact, but much of this data is not natively available to the semantic web. Data is typically collected and stored with free-text annotations in spreadsheets, many of which do not conform to existing metadata standards and are often not publically released. Along with initiatives to promote more data sharing, one of the main challenges is therefore to semantically annotate and extract this data so that it is available to the research community. Data annotation and curation are expensive and undervalued tasks that have enormous benefits to the discipline as a whole, but fewer benefits to the individual data producers. By embedding semantic annotation into spreadsheets, however, and automatically extracting this data into RDF at the time of repository submission, the process of producing standards-compliant data, that is available for semantic web querying, can be achieved without adding additional overheads to laboratory data management. This paper describes these strategies in the context of semantic data management in the SEEK. The SEEK is a web-based resource for sharing and exchanging Systems Biology data and models that is underpinned by the JERM ontology (Just Enough Results Model), which describes the relationships between data, models, protocols and experiments. The SEEK was originally developed for SysMO, a large European Systems Biology consortium studying micro-organisms, but it has since had widespread adoption across European Systems Biology.

Editor: David Hutchison and Takeo Kanade and Josef Kittler and Jon M. Kleinberg and Friedemann Mattern and John C. Mitchell and Moni Naor and Oscar Nierstrasz and C. Pandu Rangan and Bernhard Steffen and Madhu Sudan and Demetri Terzopoulos and Doug Tygar and Moshe Y. Vardi and Gerhard Weikum and Camille Salinesi and Moira C. Norrie and Óscar Pastor

Date Published: 2013

Publication Type: Journal

My data are your data

Abstract (Expand)

Encouraging more broad and inclusive data sharing in today's world will involve concerted community efforts to overcome technical barriers and human foibles. Vivien Marx investigates. (includes …s comments from Carole Goble, and mentions SysMO, SEEK and RightField).

Author: Vivien Marx

Date Published: 7th Jun 2012

Publication Type: Not specified

Populous: a tool for building OWL ontologies from templates

Abstract (Expand)

BACKGROUND: Ontologies are being developed for the life sciences to standardise the way we describe and interpret the wealth of data currently being generated. As more ontology based applications begin … to emerge, tools are required that enable domain experts to contribute their knowledge to the growing pool of ontologies. There are many barriers that prevent domain experts engaging in the ontology development process and novel tools are needed to break down these barriers to engage a wider community of scientists. RESULTS: We present Populous, a tool for gathering content with which to construct an ontology. Domain experts need to add content, that is often repetitive in its form, but without having to tackle the underlying ontological representation. Populous presents users with a table based form in which columns are constrained to take values from particular ontologies. Populated tables are mapped to patterns that can then be used to automatically generate the ontology's content. These forms can be exported as spreadsheets, providing an interface that is much more familiar to many biologists. CONCLUSIONS: Populous's contribution is in the knowledge gathering stage of ontology development; it separates knowledge gathering from the conceptualisation and axiomatisation, as well as separating the user from the standard ontology authoring environments. Populous is by no means a replacement for standard ontology editing tools, but instead provides a useful platform for engaging a wider community of scientists in the mass production of ontology content.

Authors: Simon Jupp, Matthew Horridge, Luigi Iannone, Julie Klein, , Joost Schanstra, , Robert Stevens

Date Published: 25th Jan 2012

Publication Type: Not specified

RightField: Scientific Knowledge Acquisition by Stealth through Ontology-Enabled Spreadsheets

Abstract (Expand)

RightField is a Java application that provides a mechanism for embedding ontology annotation support for scientific data in Microsoft Excel or Open Office spreadsheets. The result is semantic annotation … by stealth, with an annotation process that is less error-prone, more efficient, and more consistent with community standards. By automatically generating RDF statements for each cell a rich, Linked Data querying environment allows scientists to search their data and other Linked Data resources interchangeably, and caters for queries across heterogeneous spreadsheets. RightField has been developed for Systems Biologists but has since adopted more widely. It is open source (BSD license) and freely available from http://www.rightfield.org.uk

Authors: Katy Wolstencroft, Stuart Owen, Matthew Horridge, Wolfgang Mueller, Finn Bacall, Jacky Snoep, Franco du Preez, Quyen Nguyen, Olga Krebs, Carole Goble

Date Published: 2012

Publication Type: Journal

RightField: embedding ontology annotation in spreadsheets.

Abstract (Expand)

MOTIVATION: In the Life Sciences, guidelines, checklists and ontologies describing what metadata is required for the interpretation and reuse of experimental data are emerging. Data producers, however, … may have little experience in the use of such standards and require tools to support this form of data annotation. RESULTS: RightField is an open source application that provides a mechanism for embedding ontology annotation support for Life Science data in Excel spreadsheets. Individual cells, columns or rows can be restricted to particular ranges of allowed classes or instances from chosen ontologies. The RightField-enabled spreadsheet presents selected ontology terms to the users as a simple drop-down list, enabling scientists to consistently annotate their data. The result is 'semantic annotation by stealth', with an annotation process that is less error-prone, more efficient, and more consistent with community standards. AVAILABILITY AND IMPLEMENTATION: RightField is open source under a BSD license and freely available from http://www.rightfield.org.uk

Authors: , , Matthew Horridge, , , , ,

Date Published: 15th Jul 2011

Publication Type: Journal

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