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A space managed by WorkflowHub administrators for teams that don't want/need to manage their own space.

Teams: IBISBA Workflows, NMR Workflow, UNLOCK, NanoGalaxy, Galaxy Climate, PNDB, IMBforge, COVID-19 PubSeq: Public SARS-CoV-2 Sequence Resource, LBI-RUD, Nick-test-team, usegalaxy-eu, Italy-Covid-data-Portal, UX trial team, Integrated and Urban Plant Pathology Laboratory, SARS-CoV-2 Data Hubs, lmjxteam2, virAnnot pipeline, Ay Lab, iPC: individualizedPaediatricCure, Harkany Lab, MOLGENIS, EJPRD WP13 case-studies workflows, Common Workflow Language (CWL) community, Testing, SeBiMER, IAA-CSIC, MAB - ATGC, Probabilistic graphical models, GenX, Snakemake-Workflows, ODA, IPK BIT, CO2MICS Lab, FAME, CHU Limoges - UF9481 Bioinformatique / CNR Herpesvirus, Quadram Institute Bioscience - Bioinformatics, HecatombDevelopment, Institute of Human Genetics, Testing RO Crates, Test Team, Applied Computational Biology at IEG/HMGU, INFRAFRONTIER workflows, OME, TransBioNet, OpenEBench, Bioinformatics and Biostatistics (BIO2 ) Core, VIB Bioinformatics Core, CRC Cohort, ICAN, MustafaVoh, Single Cell Unit, CO-Graph, emo-bon, TestEMBL-EBIOntology, CINECA, Toxicology community, Pitagora-Network, Workflows Australia, Medizinisches Proteom-Center, Medical Bioinformatics, AGRF BIO, EU-Openscreen, X-omics, ELIXIR Belgium, URGI, Size Inc, GA-VirReport Team, The Boucher Lab, Air Quality Prediction, pyiron, CAPSID, Edinburgh Genomics, Defragmentation TS, NBIS, Phytoplankton Analysis, Seq4AMR, Workflow registry test, Read2Map, SKM3, ParslRNA-Seq: an efficient and scalable RNAseq analysis workflow for studies of differentiated gene expression, de.NBI Cloud, Meta-NanoSim, ILVO Plant Health, EMERGEN-BIOINFO, KircherLab, Apis-wings, BCCM_ULC, Dessimoz Lab, TRON gGmbH, GEMS at MLZ, Computational Science at HZDR, Big data in biomedicine, TRE-FX, MISTIC, Guigó lab, Statistical genetics, Delineating Regions-of-interest for Mass Spectrometry Imaging by Multimodally Corroborated Spatial Segmentation, WES, Bioinformatics Unit @ CRG, Bioinformatics Innovation Lab, BSC-CES, ELIXIR Proteomics, Black Ochre Data Labs, Zavolan Lab, Metabolomics-Reproducibility, Team Cardio, NGFF Tools, Bioinformatics workflows for life science, Workflows for geographic science, Pacific-deep-sea-sponges-microbiome, CSFG, SNAKE, Katdetectr, INFRAFRONTIER GmbH, PerMedCoE, Euro-BioImaging, EOSC-Life WP3 OC Team, cross RI project, ANSES-Ploufragan, SANBI Pathogen Bioinformatics, Biodata Analysis Group, DeSci Labs, Erasmus MC - Viroscience Bioinformatics, ARA-dev, Mendel Centre for Plant Genomics and Proteomics, Metagenomic tools, WorkflowEng, Polygenic Score Catalog, bpm, scNTImpute, Systems Biotechnology laboratory, Cimorgh IT solutions, MLme: Machine Learning Made Easy, Hurwitz Lab, Dioscuri TDA, Scipion CNB, System Biotechnology laboratory, yPublish - Bioinfo tools, NIH CFDE Playbook Workflow Partnership, MMV-Lab, EMBL-CBA, EBP-Nor, Evaluation of Swin Transformer and knowledge transfer for denoising of super-resolution structured illumination microscopy data, Bioinformatics Laboratory for Genomics and Biodiversity (LBGB), multi-analysis dFC, CholGen, RNA group, Plant Genomes Pipelines in Galaxy, Pathogen Genomic Laboratory, Chemical Data Lab, JiangLab, Pangenome database project, HP2NET - Framework for construction of phylogenetic networks on High Performance Computing (HPC) environment, Center for Open Bioimage Analysis, Generalized Open-Source Workflows for Atomistic Molecular Dynamics Simulations of Viral Helicases, Historical DNA genome skimming, QCDIS, Peter Menzel's Team, NHM Clark group, ESRF Workflow System (Ewoks), Kalbe Bioinformatics, Nextflow4Metabolomics, GBCS, CEMCOF, Jackson Laboratory NGS-Ops, Schwartz Lab, BRAIN - Biomedical Research on Adult Intracranial Neoplasms, Cancer Therapeutics and Drug Safety, Deepdefense, Mid-Ohio Regional Planning Commission, MGSSB, Institute for Human Genetics and Genomic Medicine Aachen, FengTaoSMU, EGA, Plant-Food-Research-Open, KrauthammerLab, Geo Workflows, grassland pDT, FunGIALab, CRIM - Computer Research Institute of Montréal, Medvedeva Lab, Metagenlab, FAIR-EASE, Protein-protein and protein-nucleic acid binding site prediction research, Culhane Lab, IDUN - Drug Delivery and Sensing, Edge Computing DAG Task Scheduling Research Group, Stratum corneum nanotexture feature detection using deep learning and spatial analysis: a non-invasive tool for skin barrier assessment, COPO, Taudière group, ErasmusMC Clinical Bioinformatics, interTwin, fluid flow modeling, EnrichDO, WorkflowResearch, Application Security - Test Crypt4GH solutions

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ParslRNA-Seq: an efficient and scalable RNAseq analysis workflow for studies of differentiated gene expression

Here we introduce a scientific workflow implementing several open-source software executed by Parsl parallel scripting language in an high-performance computing environment. We have applied the workflow to a single-cardiomyocyte RNA-seq data retrieved from Gene Expression Omnibus database. The workflow allows for the analysis (alignment, QC, sort and count reads, statistics generation) of raw RNA-seq data and seamless integration of differential expression results into a configurable script code. ...

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National Laboratory of Scientific Computing

Country: Brazil

City: Rio de Janeiro

Web page: https://www.gov.br/lncc/pt-br

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Framework para a Construção de Redes Filogenéticas em Ambiente de Computação de Alto Desempenho

HP2NET - Framework for construction of phylogenetic networks on High Performance Computing (HPC) environment

Abstract (Expand)

No presente artigo é apresentado uma avaliação de desempenho de um Framework de Redes Filogenéticas no ambiente do supercomputador Santos Dumont. O trabalho reforça os benefícios de paralelizar o …

Authors: Rafael Terra, Kary Ocaña, Carla Osthoff, Lucas Cruz, Philippe Navaux, Diego Carvalho

Date Published: 19th Oct 2022

Publication Type: InProceedings

DOI: 10.5753/wscad.2022.226366

Citation: Anais do XXIII Simpósio em Sistemas Computacionais de Alto Desempenho (WSCAD 2022),pp.73-84,Sociedade Brasileira de Computação

Created: 9th Jan 2024 at 12:54, Last updated: 9th Jan 2024 at 12:57

Framework para execução de workflows de redes filogenéticas em ambientes de computação de alto desempenho

HP2NET - Framework for construction of phylogenetic networks on High Performance Computing (HPC) environment

Abstract (Expand)

In the last years, the development of technologies, such as next-generation sequencing and high-performance computing allowed the execution of Bioinformatics experiments of high complexity and … computationally intensives. Different Bioinformatics fields need to use high-performance computing platforms to take advantage of the parallelism and tasks distribution, through specialized technologies of scientific workflows management systems. One of the Bioinformatics fields that need high-performance computing is phylogeny, a field that expresses the evolutive relations between genes and organisms, establishing which of them are most related evolutively. The phylogeny is used in several approaches, such as in the species classification; in the discovery of individuals’ kinship; in the identification of pathogens origins, and even in conservation biology. A way of representing these phylogenetic relations is using phylogenetic networks. However, the construction of these networks uses computationally intensive algorithms that require the constant manipulation of different input data. This work aims the development of a framework for construction of explicit phylogenetic networks, modeling a scientific workflow that adds different methods for the construction of the networks and the required input data treatment. The framework was developed to allow the use of multiple flows from the workflow in an automated, parallel, and distributed manner in a single execution and also to be executable in high- performance computing environments, constituting a challenging task, once the tools used are not developed focused in this environment. To orchestrate the workflow tasks, the scalable parallel programing library Parsl was used, allowing to do optimizations in the workflow’s tasks execution, performing better management of the resources. Two versions of the framework were developed, called Single Partition and Multi Partition, differing in the manner in which the resources are used. In tests performed, there was an improvement in the execution time of about five times when compared to the sequential execution of a flow without the optimizations. The framework was validated using public data of Dengue virus genomes, which were processed, annotated, and executed in the framework using the Santos Dumont supercomputer. The construction of the genomes’ explicit phylogenetic networks indicates that the framework is a functional, efficient, and easy to use tool.

Authors: Rafael Terra, Kary Ocaña, Carla Osthoff, Diego Carvalho

Date Published: 18th Feb 2022

Publication Type: Master's Thesis

Citation: TERRA, R. S. Framework para execução de workflows de redes filogenéticas em ambientes de computação de alto desempenho. 2022. 71 f. Tese. (Programa de Pós-Graduação em Modelagem Computacional) - Laboratório Nacional de Computação Científica, Petrópolis, 2022.

Created: 9th Jan 2024 at 13:16

Gerência e Análises de Workflows aplicados a Redes Filogenéticas de Genomas de Dengue no Brasil

HP2NET - Framework for construction of phylogenetic networks on High Performance Computing (HPC) environment

Abstract (Expand)

Processos evolutivos e dispersão de genomas de Dengue no Brasil são relevantes na direção do impacto e vigilância endemo-epidêmico e social de arboviroses emergentes. Árvores e redes filogenéticas …

Authors: Rafael Terra, Micaella Coelho, Lucas Cruz, Marco Garcia-Zapata, Luiz Gadelha, Carla Osthoff, Diego Carvalho, Kary Ocaña

Date Published: 18th Jul 2021

Publication Type: InProceedings

DOI: 10.5753/bresci.2021.15788

Citation: Anais do XV Brazilian e-Science Workshop (BRESCI 2021),pp.49-56,Sociedade Brasileira de Computação

Created: 9th Jan 2024 at 12:55, Last updated: 9th Jan 2024 at 12:56

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RNAseq_UMG_SDumont_v1

ParslRNA-Seq: an efficient and scalable RNAseq analysis workflow for studies of differentiated gene expression

RNAseq workflow UMG: Here we introduce a scientific workflow implementing several open-source software executed by Galaxy parallel scripting language in an high-performance computing environment. We have applied the workflow to a single-cardiomyocyte RNA-seq data retrieved from Gene Expression Omnibus database. The workflow allows for the analysis (alignment, QC, sort and count reads, statistics generation) of raw RNA-seq data and seamless integration of differential expression results into a ...

Type: Galaxy

Creator: Kary Ocaña

Submitter: Kary Ocaña

DOI: 10.48546/workflowhub.workflow.412.1

Created: 6th Dec 2022 at 19:22

ParslRNA-seq Scientific Workflow

ParslRNA-Seq: an efficient and scalable RNAseq analysis workflow for studies of differentiated gene expression

(Show All)

RNA-seq Scientific Workflow

Workflow for RNA sequencing using the Parallel Scripting Library - Parsl.

Reference: Cruz, L., Coelho, M., Terra, R., Carvalho, D., Gadelha, L., Osthoff, C., & Ocaña, K. (2021). Workflows Científicos de RNA-Seq em Ambientes Distribuídos de Alto Desempenho: Otimização de Desempenho e Análises de Dados de Expressão Diferencial de Genes. In Anais do XV Brazilian e-Science Workshop, p. 57-64. Porto Alegre: SBC. DOI: https://doi.org/10.5753/bresci.2021.15789 ...

Type: Unrecognized workflow type

Creators: Lucas Cruz, Luiz Gadelha, Kary Ocaña

Submitter: Kary Ocaña

DOI: 10.48546/workflowhub.workflow.411.1

Created: 6th Dec 2022 at 19:17

Kary Ocaña

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RNA-seq Scientific Workflow