Workflows

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829 Workflows visible to you, out of a total of 902
Laserfarm Jupyter Notebooks for Reserve Naturelle Nationale du Bagnas
Stable

Laserfarm (https://doi.org/10.1016/j.ecoinf.2022.101836) is a high-throughput workflow for generating geospatial data products of ecosystem structure using LiDAR point clouds from national or regional airborne laser scanning (ALS) surveys. The workflow example here shows the application of the Laserfarm workflow to the 7.5 km2 large Reserve Naturelle Nationale du Bagnas ('Bagnas') in France (3.514360 E, 43.314332 N). The work has been performed in the context of the EU project MAMBO (Modern ...

Type: Jupyter

Creators: W. Daniel Kissling, Wessel Mulder, Jinhu Wang, Yifang Shi

Submitter: W. Daniel Kissling

DOI: 10.48546/workflowhub.workflow.1297.1

Laserfarm Jupyter Notebooks for Comino
Stable

Laserfarm (https://doi.org/10.1016/j.ecoinf.2022.101836) is a high-throughput workflow for generating geospatial data products of ecosystem structure using LiDAR point clouds from national or regional airborne laser scanning (ALS) surveys. The workflow example here shows the application of the Laserfarm workflow to the 3.5 km2 large island of Comino in Malta (36.0113 E, 14.3362 N). The work has been performed in the context of the EU project MAMBO (Modern Approaches to the Monitoring of Biоdiversity, ...

Type: Jupyter

Creators: W. Daniel Kissling, Wessel Mulder, Jinhu Wang, Yifang Shi

Submitter: W. Daniel Kissling

DOI: 10.48546/workflowhub.workflow.1298.1

Laserfarm Jupyter Notebooks for Knepp Estate
Stable

Laserfarm (https://doi.org/10.1016/j.ecoinf.2022.101836) is a high-throughput workflow for generating geospatial data products of ecosystem structure using LiDAR point clouds from national or regional airborne laser scanning (ALS) surveys. The workflow example here shows the application of the Laserfarm workflow to the 5.55 km2 large Knepp Estate in the United Kingdom (0.3758 W, 50.969859 N). The work has been performed in the context of the EU project MAMBO (Modern Approaches to the Monitoring ...

Type: Jupyter

Creators: W. Daniel Kissling, Wessel Mulder, Jinhu Wang, Yifang Shi

Submitter: W. Daniel Kissling

DOI: 10.48546/workflowhub.workflow.1299.1

Laserfarm Jupyter Notebooks for Mols Bjerge National Park
Stable

Laserfarm (https://doi.org/10.1016/j.ecoinf.2022.101836) is a high-throughput workflow for generating geospatial data products of ecosystem structure using LiDAR point clouds from national or regional airborne laser scanning (ALS) surveys. The workflow example here shows the application of the Laserfarm workflow to the 1.29 km2 large Mols Bjerge National Park in Denmark (10.478393 E, 56.289050 N). The work has been performed in the context of the EU project MAMBO (Modern Approaches to the Monitoring ...

Type: Jupyter

Creators: W. Daniel Kissling, Wessel Mulder, Jinhu Wang, Yifang Shi

Submitter: W. Daniel Kissling

DOI: 10.48546/workflowhub.workflow.1300.1

Laserfarm Jupyter Notebooks for Monks Wood
Stable

Laserfarm (https://doi.org/10.1016/j.ecoinf.2022.101836) is a high-throughput workflow for generating geospatial data products of ecosystem structure using LiDAR point clouds from national or regional airborne laser scanning (ALS) surveys. The workflow example here shows the application of the Laserfarm workflow to the 0.08 km2 large Monks Wood in the United Kingdom (10.478393 E, 56.289050 N). The work has been performed in the context of the EU project MAMBO (Modern Approaches to the Monitoring ...

Type: Jupyter

Creators: W. Daniel Kissling, Wessel Mulder, Jinhu Wang, Yifang Shi

Submitter: W. Daniel Kissling

DOI: 10.48546/workflowhub.workflow.1301.1

Laserfarm Jupyter Notebooks for Oostvaardersplassen
Stable

Laserfarm (https://doi.org/10.1016/j.ecoinf.2022.101836) is a high-throughput workflow for generating geospatial data products of ecosystem structure using LiDAR point clouds from national or regional airborne laser scanning (ALS) surveys. The workflow example here shows the application of the Laserfarm workflow to the 54 km2 large Oostvaardersplassen in the Netherlands (5.418842 E, 52.456870 N). The work has been performed in the context of the EU project MAMBO (Modern Approaches to the Monitoring ...

Type: Jupyter

Creators: W. Daniel Kissling, Wessel Mulder, Jinhu Wang, Yifang Shi

Submitter: W. Daniel Kissling

DOI: 10.48546/workflowhub.workflow.1302.1

Laserfarm Jupyter Notebooks for Salisbury Plain
Stable

Laserfarm (https://doi.org/10.1016/j.ecoinf.2022.101836) is a high-throughput workflow for generating geospatial data products of ecosystem structure using LiDAR point clouds from national or regional airborne laser scanning (ALS) surveys. The workflow example here shows the application of the Laserfarm workflow to the 7.95 km2 large Salisbury Plain in the United Kingdom (1.866189 W, 51.220814 N). The work has been performed in the context of the EU project MAMBO (Modern Approaches to the Monitoring ...

Type: Jupyter

Creators: W. Daniel Kissling, Wessel Mulder, Jinhu Wang, Yifang Shi

Submitter: W. Daniel Kissling

DOI: 10.48546/workflowhub.workflow.1303.1

gromacs-dctmd/main

Perform dcTMD free energy simulations and calculations

Type: Galaxy

Creators: Simon Bray, Simon Bray

Submitter: WorkflowHub Bot

CWL4IncorporateTSSintoGXF (paired-end file)

License GitHub last commit (branch) run with docker Lab Website

 

CWL4IncorporateTSSintoGXF

This ...

Type: Common Workflow Language

Creators: Ryo Nozu, Sora Yonezawa

Submitter: Sora Yonezawa

NGS Equimolar Pooling Calculator
Stable

NGS Equimolar Pooling Calculator

A web-based tool for calculating equimolar pooling volumes from complex sub-pools for Next-Generation Sequencing (NGS).

About

This calculator helps researchers determine the correct volumes to take from each pool when combining multiple complex sub-pools of NGS libraries for sequencing. It ensures that each individual sample contributes an equal number of molecules to the final sequencing run, resulting in more balanced coverage.

Features

  • Calculate ...

Type: Unrecognized workflow type

Creator: Ben Price

Submitter: Ben Price

DOI: 10.48546/workflowhub.workflow.1344.1

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