Workflows
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Description
Historical executable generation of the NEXUS CORTEX lifecycle workflow for the zero-entropy-lab research software lineage, recorded from repository state 12287364d5915b4e51a6146996d6d8a95d547c22 on 2026-10-07.
The workflow implements a graph-based, bounded research lifecycle with read-only validation and guarded application paths. It validates runtime contracts and active ledgers, harvests and projects approved external evidence, canonicalizes the active graph, rebuilds and ingests ...
Historical executable generation of the NEXUS CORTEX lifecycle workflow for the welcome-to-github research software lineage, recorded from repository state 0b2e45c0b2eff554cf40431ce3c53693d86bc290 on 2026-10-07.
The workflow implements a graph-based, bounded research lifecycle with read-only validation and guarded application paths. It validates runtime contracts and active ledgers, harvests and projects approved external evidence, canonicalizes the active graph, rebuilds and ingests memory, ...
Technical explanation of federated execution on ASPIRE nodes (Spain, Germany, and Italy) using Pulsar.
Identification of the binding sites of the T-cell acute lymphocytic leukemia protein 1 (TAL1)
Associated Tutorial
This workflows is part of the tutorial Identification of the binding sites of the T-cell acute lymphocytic leukemia protein 1 (TAL1), available in the GTN
Features
- Includes [Galaxy Workflow ...
A common ChIP-seq workflow based on Formation of the Super-Structures on the Inactive X, https://gxy.io/GTN:T00140
Associated Tutorial
This workflows is part of the tutorial Formation of the Super-Structures on the Inactive X, available in the GTN
Features
- Includes [Galaxy Workflow ...
Tests Not available
Jupyter nootebook workflow of standard setup of protein in water simulation in Gromacs. It creates simulation box, adds solvent and counterions, sets up force field and water model, performs restrained energy minimization, NVT, and NPT equilibration, yielding inputs for a production MD run.
Designed to be used with for MDDashboard
Jupyter nootebook workflow of standard setup of protein in water simulation in Gromacs. It creates simulation box, adds solvent and counterions, sets up force field and water model, performs restrained energy minimization, NVT, and NPT equilibration, yielding inputs for a production MD run.
Designed to be used with for MDDashboard
This workflow performs DNA sequence classification using an LSTM neural network to generate predicted labels from test DNA sequences
The aim of this workflow is to handle the routine part of shotgun metagenomics data processing on Galaxy Australia.
The workflow is using the tools MetaPhlAn2 for taxonomy classification and HUMAnN2 for functional profiling of the metagenomes. The workflow is based on the Galaxy Training tutorial 'Analyses of metagenomics data - The global picture' (Saskia Hiltemann, Bérénice Batut) https://training.galaxyproject.org/training-material/topics/metagenomics/tutorials/general-tutorial/tutorial.html#shotgun-metagenomics-data. ...
Type: Galaxy
Creators: Valentine Murigneux, Mike Thang, Saskia Hiltemann, Bérénice Batut, The workflow is based on the Galaxy Training tutorial Analyses of metagenomics data. Thank you to the Galaxy Australia team, Igor Makunin and Mike Thang for help with the workflow
Submitter: Valentine Murigneux
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