Workflows

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831 Workflows visible to you, out of a total of 904
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

Gene Fetch
Work-in-progress

Gene_fetch

This tool fetches gene sequences from NCBI databases based on taxonomy IDs (taxids) or taxonomic information. It can retrieve both protein and nucleotide sequences for various genes, including protein-coding genes (e.g., cox1, cytb, rbcl, matk) and rRNA genes (e.g., 16S, 18S).

Feature highlight

  • Fetch protein and/or nucleotide sequences from NCBI GenBank database.
  • Handles both direct nucleotide sequences and protein-linked nucleotide searches (CDS extraction includes fallback ...

Type: Python

Creators: Dan Parsons, Ben Price

Submitter: Dan Parsons

Gene Fetch

Gene_fetch

This tool fetches gene sequences from NCBI databases based on taxonomy IDs (taxids) or taxonomic information. It can retrieve both protein and nucleotide sequences for various genes, including protein-coding genes (e.g., cox1, cytb, rbcl, matk) and rRNA genes (e.g., 16S, 18S).

Feature highlight

  • Fetch protein and/or nucleotide sequences from NCBI GenBank database.
  • Handles both direct nucleotide sequences and protein-linked nucleotide searches (CDS extraction includes fallback ...

Type: Python

Creators: Dan Parsons, Ben Price

Submitter: Dan Parsons

nf-core/hlatyping

GitHub Actions CI Status GitHub Actions Linting StatusAWS CI[![Cite ...

Type: Nextflow

Creators: Christopher Mohr, Alexander Peltzer, Sven Fillinger

Submitter: WorkflowHub Bot

gSpreadComp

gSpreadComp: Streamlining Microbial Community Analysis for Resistance, Virulence, and Plasmid-Mediated Spread

Overview

gSpreadComp is a UNIX-based, modular bioinformatics toolkit designed to streamline comparative genomics for analyzing microbial communities. It integrates genome annotation, gene spread calculation, plasmid-mediated horizontal gene transfer (HGT) detection and resistance-virulence ranking within the analysed microbial community to help researchers identify potential ...

Type: Shell Script

Creator: Jonas Kasmanas

Submitter: Jonas Kasmanas

DOI: 10.48546/workflowhub.workflow.1340.3

COMPSs Matrix Multiplication resourceUsage profiling example MN5 MSIZE=20 BSIZE=768 7 Nodes total
Stable

COMPSs Matrix Multiplication resourceUsage profiling example.

MN5 MSIZE=20 BSIZE=768 7 Nodes (6 workers) (--num_nodes=7 --worker_in_master_cpus=0).

  • Total number of tasks: 20^3 = 8000
  • Maximum code parallelism: 20^2 = 400
  • Total cores: 112*6 = 672
  • Maximum utilisation: 400 / 112 = 3,57 Nodes

Overall stats from "pycompss inspect":

│ └── overall 
│ ├── matmul_tasks 
│ │ └── multiply 
│ │ ├── maxTime = 91,111 ms 
│ │ ├── executions = 8,000 
│ │ ├── avgTime = 84,839 ms 
│ │ └── minTime = 79,278 ms
...

Type: COMPSs

Creators: Raül Sirvent, Rosa M Badia

Submitter: Raül Sirvent

Matrix Multiplication – resource usage visualization

Application that perform the multiplication between matrices. In this experiment, a new profiling visualization is available, showing the resource usage such as CPU, memory, data read and written to disk, and data sent and received over the network.

Type: COMPSs

Creators: Raül Sirvent, Nicolò Giacomini

Submitter: Nicolò Giacomini

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