Expertise: Bioinformatics
Tools: R, Transcriptomics
Teams: Cimorgh IT solutions
Organizations: cimorgh IT
Expertise: Bioinformatics, Genomics, Metagenomics, Microbiology, NGS, Python, R, bash, WDL
Tools: Mathematical Modelling, R, WDL
Expertise: Bioinformatics, Metabarcoding, Metagenomics, Microbiology
Teams: EOSC-Life WP3 OC Team, cross RI project, EOSC-Life WP3, Euro-BioImaging
Organizations: EOSC-Life, Euro-BioImaging
Expertise: Bioengineering, Bioinformatics, Computer Science, Data Management
Tools: Databases, Jupyter notebook, Python
Biomedical Engineer working on preclinical image dataset repository and cross researching RIs
Expertise: Bioinformatics, Genomics, Scientific workflow developement
Expertise: Bioinformatics, Genomics, Machine Learning
Tools: Python, R, Machine Learning
I am a Ph.D. student in Gong lab. I am interested in cancer genomics, including the mining of genetic risk determinants in cancer, functional prediction of genetic variants, tumor-associated molecular epidemiology, large-scale data integration, analysis, and mining, as well as the construction of bioinformatical data platforms.
Expertise: Bioinformatics
Expertise: Bioinformatics, Cheminformatics, Software Engineering, Metabolomics, Lipidomics
Expertise: Bioinformatics, Genomics, Metagenomics, Data Management
Tools: CWL, Jupyter notebook, Nextflow, Molecular Biology, Workflows, Microbiology, Transcriptomics, Perl, Python, R
Teams: EU-Openscreen
Organizations: Fraunhofer Institute for Translational Medicine and Pharmacology ITMP

Expertise: Bioinformatics, Cheminformatics, Machine Learning
Tools: Workflows
I am a bioinformatician and phylogenetics. I really love working on problems at the intersection of high-performance computing and scientific workflows applied to omics
Expertise: Bioinformatics, Computer Science, Data Management, Genetics, Genomics, Machine Learning, Metagenomics, NGS, Scientific workflow developement, Software Engineering
Tools: Databases, Galaxy, Genomics, Jupyter notebook, Machine Learning, Nextflow, nf-core, PCR, Perl, Python, R, rtPCR, Snakemake, Transcriptomics, Virology, Web, Web services, Workflows
Dad, husband and PhD. Scientist, technologist and engineer. Bibliophile. Philomath. Passionate about science, medicine, research, computing and all things geeky!
Expertise: Bioinformatics, Molecular Biology, Computer Science, NGS, Software Engineering
Teams: EU-Openscreen, OME
Organizations: Fraunhofer Institute for Translational Medicine and Pharmacology ITMP

Expertise: Cheminformatics, Bioinformatics
Teams: Bioinformatics Innovation Lab
Organizations: Pondicherry University

Expertise: Bioinformatics, Systems Biology, Machine Learning
Tools: Galaxy, Cytoscape, Databases, Jupyter notebook, R, Python
Ph.D. Student at Department of Bioinformatics, Pondicherry University
Teams: MAB - ATGC
Organizations: Centre National de la Recherche Scientifique (CNRS)

Expertise: Bioinformatics, Genomics, algorithm, Machine Learning, Metagenomics, NGS, Computer Science
Tools: Transcriptomics, Genomics, Python, C/C++, Web services, Workflows
Expertise: Bioinformatics, Biostatistics, Metabarcoding, Metagenomics
Teams: Harkany Lab
Organizations: Medical University of Vienna

Expertise: Systems Biology, Bioengineering, Bioinformatics, Neuroscience
Tools: Workflows, Machine Learning, Transcriptomics
Teams: GalaxyProject SARS-CoV-2, nf-core viralrecon, EOSC-Life - Demonstrator 7: Rare Diseases, iPC: individualizedPaediatricCure, EJPRD WP13 case-studies workflows, TransBioNet, OpenEBench, ELIXIR Proteomics
Organizations: Barcelona Supercomputing Center (BSC-CNS), ELIXIR

Expertise: Bioinformatics, Computer Science, AI, Machine Learning
Computer Engineer in Barcelona Supercomputing Center (BSC)
Expertise: Bioinformatics
Bioinformatician in Stockholm, Sweden. Lead for nf-core and MultiQC projects.
Teams: GalaxyProject SARS-CoV-2
Organizations: Earlham Institute

Expertise: Bioinformatics
Tools: Galaxy
Teams: V-Pipe
Organizations: SIB - Swiss Institute of Bioinformatics

Expertise: Bioinformatics, Software Engineering
Medical doctor and bioinformatician
Developer from the Swiss Institute of Bioinformatics (SIB) Working at the Computational Biology Group (CBG) of ETH Zurich.
Diplom in Medicine. MSc in Bioinformatics and Proteomics.
I am also a ski teacher as a hobby.
Research Director @ INRAe
Teams: IBISBA Workflows
Organizations: Unspecified
Expertise: Bioinformatics
Tools: Workflows, Web services, Python
Teams: GalaxyProject SARS-CoV-2
Organizations: BC Centre for Disease Control

Expertise: Bioinformatics, Data Management, Molecular Biology
Tools: Databases, PCR, Workflows, Web services
This workflow represents the Default ML Pipeline for AutoML feature from MLme. Machine Learning Made Easy (MLme) is a novel tool that simplifies machine learning (ML) for researchers. By integrating four essential functionalities, namely data exploration, AutoML, CustomML, and visualization, MLme fulfills the diverse requirements of researchers while eliminating the need for extensive coding efforts. MLme serves as a valuable resource that empowers researchers of all technical levels to leverage ...
CLAWS (CNAG's Long-read Assembly Workflow in Snakemake)
Snakemake Pipeline used for de novo genome assembly @CNAG. It has been developed for Snakemake v6.0.5.
It accepts Oxford Nanopore Technologies (ONT) reads, PacBio HFi reads, illumina paired-end data, illumina 10X data and Hi-C reads. It does the preprocessing of the reads, assembly, polishing, purge_dups, scaffodling and different evaluation steps. By default it will preprocess the reads, run Flye + Hypo + purge_dups + yahs and evaluate ...
Type: Snakemake
Creators: Jessica Gomez-Garrido, Fernando Cruz (CNAG), Francisco Camara (CNAG), Tyler Alioto (CNAG)
Submitter: Jessica Gomez-Garrido
About SnakeMAGs
SnakeMAGs is a workflow to reconstruct prokaryotic genomes from metagenomes. The main purpose of SnakeMAGs is to process Illumina data from raw reads to metagenome-assembled genomes (MAGs). SnakeMAGs is efficient, easy to handle and flexible to different projects. The workflow is CeCILL licensed, implemented in Snakemake (run on multiple cores) and available ...
GERONIMO
Introduction
GERONIMO is a bioinformatics pipeline designed to conduct high-throughput homology searches of structural genes using covariance models. These models are based on the alignment of sequences and the consensus of secondary structures. The pipeline is built using Snakemake, a workflow management tool that allows for the reproducible execution of analyses on various computational platforms.
The idea for developing GERONIMO emerged from a comprehensive search for [telomerase ...
prepareChIPs
This is a simple snakemake
workflow template for preparing single-end ChIP-Seq data.
The steps implemented are:
- Download raw fastq files from SRA
- Trim and Filter raw fastq files using
AdapterRemoval
- Align to the supplied genome using
bowtie2
- Deduplicate Alignments using
Picard MarkDuplicates
- Call Macs2 Peaks using
macs2
A pdf of the rulegraph is available here
Full details for each step are given below. Any additional ...
SINGLE-END workflow. Align reads on fasta reference/assembly using bwa mem, get a consensus, variants, mutation explanations.
IMPORTANT:
- For "bcftools call" consensus step, the --ploidy file is in "Données partagées" (Shared Data) and must be imported in your history to use the worflow by providing this file (tells bcftools to consider haploid variant calling).
- SELECT the mot ADAPTED VADR MODEL for annotation (see vadr parameters).
This repository hosts Metabolome Annotation Workflow (MAW). The workflow takes MS2 .mzML format data files as an input in R. It performs spectral database dereplication using R Package Spectra and compound database dereplication using SIRIUS OR MetFrag . Final candidate selection is done in Python using RDKit and PubChemPy.
Type: Common Workflow Language
Creators: Mahnoor Zulfiqar, Michael R. Crusoe, Luiz Gadelha, Christoph Steinbeck, Maria Sorokina, Kristian Peters
Submitter: Mahnoor Zulfiqar
Oxford Nanopore QC pipeline which calculates basic statistics as well as filtering for longest reads and creating QC plots using Nanoplots
PacBio HiFi QC pipeline calculates basic read statistics such as length and yield as well as running FastQC and CutAdapt before accumulating all results with MultiQC
MGnify genomes analysis pipeline
MGnify A pipeline to perform taxonomic and functional annotation and to generate a catalogue from a set of isolate and/or metagenome-assembled genomes (MAGs) using the workflow described in the following publication:
Gurbich TA, Almeida A, Beracochea M, Burdett T, Burgin J, Cochrane G, Raj S, Richardson L, Rogers AB, Sakharova E, Salazar GA and Finn RD. (2023) [MGnify Genomes: A Resource for Biome-specific Microbial Genome ...
GermlineStructuralV-nf
:wrench: This pipeline is currently under development :wrench:
- Description
- Diagram
- User guide
- Infrastructure usage and recommendations
- Benchmarking
- Workflow summaries
- Metadata
- Component tools
- Additional notes
- Help/FAQ/Troubleshooting
...
Type: Nextflow
Creators: Georgina Samaha, Marina Kennerson, Tracy Chew, Sarah Beecroft
Submitter: Georgina Samaha
Type: Nextflow
Creators: Pablo Riesgo Ferreiro, Thomas Bukur, Patrick Sorn
Submitter: Pablo Riesgo Ferreiro
IndexReferenceFasta-nf
===========
Collection of de-novo genome assembly workflows written for implementation in Galaxy
Input data should be PacBio HiFi reads and Illumina 3-dimensional Chromatin Confirmation Capture (HiC) reads
Executing all workflows will output two, scaffolded, haplotype assemblies
Maintainers: Tom Brown, Diego De Panis
Number of items: 6
Tags: Assembly, Bioinformatics, Galaxy, Genomics, ONT, Genome assembly, HiFi