Visual Workflow Tools
Visual Workflow Tools - Related Videos
09:23
Integrating Automated Simulation Workflows with 3D Visualization for Virtual Experiments in the Metaverse
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2026
A generalized, FAIR-compliant method is presented for domain-expert researchers seeking to integrate simulation and data-processing tools into automated workflows for 3D virtual experiments. A neutronics example demonstrates setting up a local Galaxy instance, wrapping OpenMC and file-conversion tools, launching workflows from Omniverse, and visualizing the converted 3D outputs.
06:29
Workflow and Tools for Crystallographic Fragment Screening at the Helmholtz-Zentrum Berlin
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Cited by 19 •
2021
Crystallographic fragment screening at the Helmholtz-Zentrum Berlin is performed using a workflow with dedicated compound libraries, crystal handling tools, fast data collection facilities and largely automated data analysis. The presented protocol intends to maximize the output of such experiments to provide promising starting points for downstream structure-based ligand design.
07:12
Alphavirus Transducing System: Tools for Visualizing Infection in Mosquito Vectors
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Cited by 11 •
2010
Methods for using alphavirus transducing systems to express fluorescent reporters in vitro and in adult mosquitoes are described. This technique may be adapted to express any protein of interest in lieu of or in addition to a reporter.
05:36
STFEEG-Tool: A Spatial-Temporal-Frequency EEG Analysis Tool for Motor Imagery Brain-Computer Interfaces
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2026
This study presents a standardized and reproducible protocol for implementing the Spatial-Temporal-Frequency EEG analysis tool (STFEEG) for motor imagery EEG decoding, incorporating configurable spatial-temporal-frequency segmentation, Common Spatial Patterns (CSP)-based feature extraction, multiple classification algorithms, and visualization capabilities.
11:39
A Quantitative Fitness Analysis Workflow
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Cited by 25 •
2012
Quantitative Fitness Analysis (QFA) is a complementary series of experimental and computational methods for estimating microbial culture fitnesses. QFA estimates the effect of genetic mutations, drugs or other applied treatments on microbe growth. Experiments scaling from focussed analysis of single cultures to thousands of parallel cultures can be designed.
FAQs
Branching logic represents alternative paths that can follow a behavioral event, decision, or experimental condition. Each branch links a possible input to a corresponding action or outcome, allowing researchers to inspect where processes diverge. This structure helps clarify decision sequences and makes alternative behavioral responses easier to compare, communicate, and analyze.
Nodes can represent tasks, observations, decisions, or outcomes, while directional links show the order or dependency between them. Together, they reveal how one behavioral event leads to another and where a process depends on a prior step. This organization helps researchers examine sequences without losing relationships among experimental or interaction components.
When behavioral steps and dependencies are laid out graphically, repeated routes and points where progress slows become easier to see. Researchers can inspect recurring paths across observations, protocols, or interactions and identify stages that repeatedly constrain the process. These findings support process refinement and can guide more consistent behavioral data collection.
Begin by identifying the relevant behavioral events, decisions, actions, and outcomes. Place these elements into connected nodes, then add directional links to show their order and branching logic to represent alternatives. Reviewing the completed map can expose missing dependencies or unclear transitions, helping researchers refine the sequence before using it for analysis or communication.
A graphical workflow can make the intended order of observations, actions, and decision points visible to everyone involved in a study. By showing dependencies and alternative paths, it gives collaborators a shared process to follow and inspect. This clarity supports more consistent data collection and makes procedural differences easier to identify during collaborative analysis.
They can map behavioral sequences, experimental protocols, decision processes, and interactions between individuals or systems. Researchers can use the resulting workflows to communicate behavioral models, examine how inputs lead to outcomes, and coordinate analysis across collaborators. The same representation also supports process refinement when recurring patterns or dependencies become apparent.