20 papers · ranked by Valyu relevance
Frédéric Suter, Tainã Coleman, İlkay Altintaş, Rosa M. Badía + 22 more
Fred´ eric Suter ´ a,∗ , Taina Coleman ˜ b,∗ , ˙Ilkay Altintas¸ b , Rosa M. Badia c , Bartosz Balis d , Kyle Chard e , Iacopo Colonnelli f , Ewa Deelman g , Paolo Di Tommaso h , Thomas Fahringer i , Carole Goble j , Shantenu Jha k , Daniel S. Katz l , Johannes Koster ¨ m, Ulf Leser n , Kshitij Mehta a , Hilary Oliver o…
Alexandre Melo, Alessandra Faria-Campos, Daiane Mariele DeLaat, Rodrigo Keller + 2 more
'Rodrigo Keller' 'Vinícius Abreu' 'Sérgio Campos'] Background The need to manage large amounts of data is a clear demand for laboratories nowadays. The use of Laboratory Information Management Systems (LIMS) to achieve this is growing each day. A LIMS is a complex computational system used to manage laboratory data…
Glória Cravo
We describe the structure of a workflow as a graph whose vertices represent tasks and the arcs are associated to workflow transitions in this paper. To each task an input/output logic operator is associated. Furthermore, we associate a Boolean term to each transition present in the workflow. We still identify the…
Stephen R. Piccolo, Zachary E. Ence, Elizabeth C. Anderson, Jeffrey T. Chang + 1 more
Command-line software plays a critical role in biology research. However, processes for installing and executing software differ widely. The Common Workflow Language (CWL) is a community standard that addresses this problem. Using CWL, tool developers can formally describe a tool’s inputs, outputs, and other execution…
Alessandro Maccagnan, Mauro Riva, Erika Feltrin, Barbara Simionati + 3 more
'Tullio Vardanega' 'Giorgio Valle' 'Nicola Cannata'] Background Laboratory protocols in life sciences tend to be written in natural language, with negative consequences on repeatability, distribution and automation of scientific experiments. Formalization of knowledge is becoming popular in science. In the case of…
Luis de la Garza, Johannes Veit, Andras Szolek, Marc Röttig + 4 more
'Stephan Aiche' 'Sandra Gesing' 'Knut Reinert' 'Oliver Kohlbacher'] Background Reproducibility is one of the tenets of the scientific method. Scientific experiments often comprise complex data flows, selection of adequate parameters, and analysis and visualization of intermediate and end results. Breaking down the…
Levi N. Naden, Sam Ellis, Shantenu Jha
Workflows in biomolecular science are very important as they are intricately intertwined with the scientific outcomes, as well as algorithmic and methodological innovations. The use and effectiveness of workflow tools to meet the needs of the biomolecular science community is varied. MolSSI co-organized a biomolecular…
Daniel Silva Junior, Esther Pacitti, Aline Paes, Daniel de Oliveira + 1 more
'Claudio Ardagna'] Scientific Workflows (SWfs) have revolutionized how scientists in various domains of science conduct their experiments. The management of SWfs is performed by complex tools that provide support for workflow composition, monitoring, execution, capturing, and storage of the data generated during…
Gordon Gibb, Nick Brown, W Rupert, Nash + 6 more
'Santiago Monedero' 'Humberto Díaz Fidalgo' 'Joaquín Ramirez' 'Adrián Cardíl' 'Max Kontak'] Abstract—In this paper we present a workflow management system which permits the kinds of data-driven workflows required by urgent computing, namely where new data is integrated into the workflow as a disaster progresses in…
Mahnoor Zulfiqar, Michael R. Crusoe, Birgitta König-Ries, Christoph Steinbeck + 2 more
Scientific workflows facilitate the automation of data analysis tasks by integrating various software and tools executed in a particular order. To enable transparency and reusability in workflows, it is essential to implement the FAIR principles. Here, we describe our experiences implementing the FAIR principles for…
Jason P. Kurs, Manuele Simi, Fabien Campagne
Computational workflows and pipelines are often created to automate series of processing steps. For instance, workflows enable one to standardize analysis for large projects or core facilities, but are also useful for individual biologists who need to perform repetitive data processing. Some workflow systems, designed…
Taylor Reiter, Phillip T. Brooks, Luiz Irber, Shannon E.K. Joslin + 4 more
As the scale of biological data generation has increased, the bottleneck of research has shifted from data generation to analysis. Researchers commonly need to build computational workflows that include multiple analytic tools and require incremental development as experimental insights demand tool and parameter…
Jay Jay Billings, Shantenu Jha
The role of scalable high-performance workflows and flexible workflow management systems that can support multiple simulations will continue to increase in importance. For example, with the end of Dennard scaling, there is a need to substitute a single long running simulation with multiple repeats of shorter…
Authors not listed
Self-driving laboratories (SDLs) promise accelerated scientific discovery and product development by closing the loop between robotic execution and AI/ML-driven decision making. In practice, however, SDL orchestration remains fragmented; workflows are typically encoded as laboratory-specific scripts or bespoke…
Samuel Lampa, Martin Dahlö, Jonathan Alvarsson, Ola Spjuth
The complex nature of biological data has driven the development of specialized software tools. Scientific workflow management systems simplify the assembly of such tools into pipelines and assist with job automation and aids reproducibility of analyses. Many contemporary workflow tools are specialized and not designed…
Anna-Lena Lamprecht, Magnus Palmblad, Jon Ison, Veit Schwämmle + 28 more
Scientific data analyses often combine several computational tools in automated pipelines, or workflows. Thousands of such workflows have been used in the life sciences, though their composition has remained a cumbersome manual process due to a lack of standards for annotation, assembly, and implementation. Recent…
Authors not listed
This paper presents GLAS (Git-based Lab Automated Scheduler or Get Lab Automation Simplified), an open-source, robust, and highly expandable Git-based architecture designed for laboratory automation. GLAS can be deployed in both partially and fully automated experimental science laboratories, enabling the development…
Peter Kraus, Edan Bainglass, Francisco F. Ramirez, Enea Svaluto-Ferro + 7 more
Compliance with good research data management practices means trust in the integrity of the data, and it is achievable by a full control of the data gathering process. In this work, we demonstrate tooling which bridges these two aspects, and illustrate its use in a case study of automated battery cycling. We…
Michael J. Jackson, Edward Wallace, Kostas Kavoussanakis
Workflow management systems represent, manage, and execute multi-step computational analyses and offer many benefits to bioinformaticians. They provide a common language for describing analysis workflows, contributing to reproducibility and to building libraries of reusable components. They can support both incremental…
Rama El-khawaldeh, Mason Guy, Finn Bork, Nina Taherimakhsousi + 6 more
This work presents a generalizable computer vision (CV) and machine learning model that is used for automated real-time monitoring and control of a diverse array of workup processes. Our system simultaneously monitors multiple physical parameters (e.g., liquid level, homogeneity, turbidity, solid, residue, and color)…