/presentations/Figure2.pdf

_p_stRT/_I_STRT pipeline

Creators: Maja Zagorscak, Marko Petek

Submitter: Maja Zagorscak

DOI: 10.15490/fairdomhub.1.datafile.3157.1

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pISA-tree - a data management framework for life science research projects using a standardised directory tree

Abstract (Expand)

Abstract We have developed pISA-tree, a straightforward and flexible data management solution for organisation of life science project-associated research data and metadata. It enables on the fly …and metadata. It enables on the fly creation of enriched directory tree structure ( p roject/ I nvestigation/ S tudy/ A ssay), via a series of sequential batch files in a standardised manner based upon the ISA metadata framework. Metadata, according to the system-provided metadata templates, is generated in parallel at each level. The system supports reproducible research and is in accordance with the Open Science initiative and FAIR principles. Compared with similar frameworks, it does not require any systems administration and maintenance as it can be run on a personal computer or network drive. It is complemented with two R packages, pisar and seekr , where the former facilitates integration of the pISA-tree datasets into bioinformatic pipelines and the latter enables synchronisation with the FAIRDOMHub public repository using the SEEK API. Source code and detailed documentation of pISA-tree and its supporting R packages are available from https://github.com/NIB-SI/pISA-tree . We demonstrate the usability of pISA-tree with two examples of medium sized life science projects. Accordingly, it is suitable and also currently used to manage larger projects including several partners from different countries. Since pISA-tree was initiated by end user requirements with an emphasis on practicality, it will facilitate adoption of FAIR data management practices and open science principles.

Authors: Marko Petek, Maja Zagorščak, Andrej Blejec, Živa Ramšak, Anna Coll, Špela Baebler, Kristina Gruden

Date Published: 21st Nov 2021

Publication Type: Journal

Data Formats for Systems Biology and Quantitative Modeling

Abstract (Expand)

Data standards support the reliable exchange of information, the interoperability of tools, and the reproducibility of scientific results. In systems biology standards are agreed ways of structuring, … describing, and associating models and data, as well as their respective parts, graphical visualization, and information about applied experimental or computational methods. Such standards also assist with describing how constituent parts interact together, or are linked, and how they are embedded in their environmental and experimental context. Here the focus will be on standards for formatting models and their content, and on metadata checklists and ontologies that support modeling.

Author: Martin Golebiewski

Date Published: 2019

Publication Type: InBook

Specifications of Standards in Systems and Synthetic Biology: Status and Developments in 2019

Abstract (Expand)

This special issue of the Journal of Integrative Bioinformatics presents an overview of COMBINE standards and their latest specifications. The standards cover representation formats for computational … modeling in synthetic and systems biology and include BioPAX, CellML, NeuroML, SBML, SBGN, SBOL and SED-ML. The articles in this issue contain updated specifications of SBGN Process Description Level 1 Version 2, SBML Level 3 Core Version 2 Release 2, SBOL Version 2.3.0, and SBOL Visual Version 2.1.

Authors: Falk Schreiber, Björn Sommer, Gary D. Bader, Padraig Gleeson, Martin Golebiewski, Michael Hucka, Sarah M. Keating, Matthias König, Chris Myers, David Nickerson, Dagmar Waltemath

Date Published: 13th Jul 2019

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

The Human Physiome: how standards, software and innovative service infrastructures are providing the building blocks to make it achievable

Abstract (Expand)

Reconstructing and understanding the Human Physiome virtually is a complex mathematical problem, and a highly demanding computational challenge. Mathematical models spanning from the molecular level … through to whole populations of individuals must be integrated, then personalized. This requires interoperability with multiple disparate and geographically separated data sources, and myriad computational software tools. Extracting and producing knowledge from such sources, even when the databases and software are readily available, is a challenging task. Despite the difficulties, researchers must frequently perform these tasks so that available knowledge can be continually integrated into the common framework required to realize the Human Physiome. Software and infrastructures that support the communities that generate these, together with their underlying standards to format, describe and interlink the corresponding data and computer models, are pivotal to the Human Physiome being realized. They provide the foundations for integrating, exchanging and re-using data and models efficiently, and correctly, while also supporting the dissemination of growing knowledge in these forms. In this paper, we explore the standards, software tooling, repositories and infrastructures that support this work, and detail what makes them vital to realizing the Human Physiome.

Authors: D. Nickerson, K. Atalag, B. de Bono, J. Geiger, C. Goble, S. Hollmann, J. Lonien, W. Muller, B. Regierer, N. J. Stanford, M. Golebiewski, P. Hunter

Date Published: 7th Apr 2016

Publication Type: Not specified

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

Licensing, Citation and Sustainability.

Prepared and presented by Carole Goble for the Reproducible and Citable Data and Models in Warnemünde, Germany. September 14th - 16th, 2015.

Creators: Natalie Stanford, Carole Goble

Submitter: Natalie Stanford

External Link
Data Management Plan

Data Management Plan (v.1.0) of the project CEPOPA.

Creator: Ioannis Pavlidis

Submitter: Ioannis Pavlidis

DOI: 10.15490/fairdomhub.1.document.690.1

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