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354 Workflows visible to you, out of a total of 384

📄 Generalizable machine learning models for rapid antimicrobial resistance prediction in unseen healthcare settings

This repository contains the code used for the experiments in the paper:

Generalizable machine learning models for rapid antimicrobial resistance prediction in unseen healthcare settings by Diane Duroux, Paul P. Meyer, Giovanni Visonà, and Niko Beerenwinkel.

⚙️ Install the dependencies

Clone the repository, unzip OriginalData.zip, and install the necessary dependencies ...

Type: Python

Creators: None

Submitter: Diane Duroux

A workflow for performing alignment and phylogeny using protein sequences when studying genes/gene families.

Type: Galaxy

Creators: None

Submitter: Avani Bhojwani

Stable

MAGNETO

MAGNETO is an automated snakemake workflow dedicated to MAG (Metagenome-Assembled Genomes) reconstruction from metagenomic data.

It includes a fully-automated coassembly step informed by optimal clustering of metagenomic distances, and implements complementary genome binning strategies, for improving MAG recovery.

Key Features

  • Quality Control (QC): Automatically assesses the quality and the contamination of input reads, ensuring that low-quality data are filtered out to improve ...

Type: Snakemake

Creators: Samuel Chaffron, Audrey Bihouee, Benjamin Churcheward, Maxime Millet, Guillaume Fertin, Hugo Lefeuvre

Submitter: Hugo Lefeuvre

DOI: 10.48546/workflowhub.workflow.1815.2

RNA-SeqEZPZ is a pipeline to run analysis of RNA-Seq experiments from raw FASTQ files all the way to differential genes analysis. The pipeline is accessible through a graphical user interface implemented using a Shiny app and features interactive plots. Advanced users have the ability to customize the scripts provided with the pipeline. This pipeline is designed to run on an HPC cluster. Please cite [1] if you are using this pipeline for a publication.

Installation

In order to use the ...

Type: Shell Script

Creators: None

Submitter: Cenny Taslim

RNA-SeqEZPZ-NF

Nextflow Pipeline for RNA-SeqEZPZ

A Point-and-Click Pipeline for Comprehensive Transcriptomics Analysis with Interactive Visualizations

RNA-SeqEZPZ-NF is another implementation of RNA-SeqEZPZ. RNA-SeqEZPZ-NF uses the same user interface as RNA-SeqEZPZ and runs the same pipeline, but runs the pipeline implemented by Nextflow. This pipeline is currently tested on HPC cluster with SLURM scheduler. Advanced ...

Type: Nextflow

Creators: None

Submitter: Cenny Taslim

Type: Galaxy

Creators: Yi Sun, Arif Khan, nfdi4bioimage

Submitter: Yi Sun

DUNE: Deep feature extraction by UNet-based Neuroimaging-oriented autoEncoder

A versatile neuroimaging encoder that captures brain complexity across multiple diseases: cancer, dementia and schizophrenia.

Overview

DUNE (Deep feature extraction by UNet-based Neuroimaging-oriented autoEncoder) is a neuroimaging-oriented deep learning model designed to extract deep features from multisequence brain MRIs, enabling their processing by basic machine learning algorithms. This project provides an ...

Type: Python

Creator: Thomas Barba

Submitter: Thomas Barba

DOI: 10.48546/workflowhub.workflow.1809.1

Stable

Description

The Settlement Delineation and Analysis (SDA) workflows generates a settlement network from geospatial settlement data. It can process geotiff and shapefile inputs and was originally designed to operate on the World Settlement Footprint dataset. Through multiple workflow stages, a settlement network is constructed, contracted (i.e. clustered) and ultimately analysed with centrality measures. The output shapefile stores the ...

Type: Docker

Creator: Lorenz Gruber

Submitter: Lorenz Gruber

DOI: 10.48546/workflowhub.workflow.1308.2

Stable

Colorectal-cancer-detection-using-ColoPola-dataset

Methods

We trained and tested three models from scratch (CNN, CNN_2 and EfficientFormerV2) and two pretrained models (DenseNet121 and EfficientNetV2-m) to classify the colorectal cancer using the ColoPola dataset.

ColoPola dataset

The dataset consists of 572 slices (specimens) with 20,592 images. There are 284 cancer samples and 288 normal samples. This dataset can download from Zenodo repository. ...

Type: Python

Creators: Thi-Thu-Hien Pham, Thao-Vi Nguyen, The-Hiep Nguyen, Quoc-Hung Phan, Thanh-Hai Le

Submitter: Thanh-Hai Le

DOI: 10.48546/workflowhub.workflow.1797.1

CryoDataBot

CryoDataBot is an automated pipeline designed to streamline dataset generation for cryogenic electron microscopy (cryoEM)-based atomic model building. It supports large-scale AI training and benchmarking by providing standardized tools for data retrieval, preprocessing, labeling, and quality control. CryoDataBot enables flexible configurations for diverse biomolecular structures, improves modeling reproducibility, and facilitates retraining of AI models such as U-Net and CryoREAD. ...

Type: Python

Creators: Qibo Xu, Hong Zhou, Leon Wu, Micahel Rebelo, Shi Feng, Star Yu, Farhanaz Farheen, Daisuke Kihara

Submitter: Qibo Xu

DOI: 10.48546/workflowhub.workflow.1796.1

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