Expertise: Bioinformatics
Tools: CWL, Genomics, Python, R, Transcriptomics, Jupyter notebook
Hiroshima University, Graduate School of Integrated Sciences for life, Laboratory of Genome Informatics, Ph.D student GitHub: https://github.com/yonesora56
Expertise: Bioinformatics, Biochemistry
Tools: Python
Expertise: Machine Learning, R, Scientific workflow developement, Workflows, Agronomy, Biostatistics
Expertise: Bioinformatics, Metagenomics, NGS, Scientific workflow developement, Software Engineering
Tools: Conda, Jupyter notebook, Python, R, Single Cell analysis, Snakemake
Teams: CRIM - Computer Research Institute of Montréal
Organizations: CRIM
https://orcid.org/0000-0003-4862-3349Expertise: AI, Machine Learning, Python, Scientific workflow developement, Software Engineering, Workflows, Geospatial, Computer Vision
Tools: CWL, Databases, Jupyter notebook, Python, Workflows, Conda, OGC
Teams: RECETOX SpecDatRI, RECETOX, usegalaxy-eu, ELIXIR Metabolomics
Organizations: Masaryk University, RECETOX
https://orcid.org/0000-0001-6744-996XExpertise: Bioinformatics, Cheminformatics, Metabolomics, Python, R, Software Engineering, Workflows
Tools: Metabolomics, Python, R, Workflows, Mass spectrometry, Chromatography
Teams: Galaxy Training Network
Organizations: Galaxy
I'm a bot managed by @hexylena to upload workflows from the Galaxy Training Network to the WorkflowHub. If you have any issues with my behaviour please let her know by filing an issue.
Expertise: High Performance Computing, Scientific workflow developement, Software Engineering, astronomy
Tools: Galaxy, Jupyter notebook, Python, Workflows, Git
Teams: AI4Life OC
Organizations: ai4life
Expertise: AI, Software Engineering, Bioimage
Tools: Python
Teams: COMPSs Tutorials
Organizations: Universitat Rovira i Virgili
https://orcid.org/0000-0002-6977-4413Expertise: Computer Science, High Performance Computing, Grid Computing
Tools: Molecular Biology, Python, OmpSs, OpenCL
Teams: Chemical Data Lab
Organizations: Department of Physical Chemistry, Faculty of Science, Palacký University Olomouc
https://orcid.org/0000-0003-0285-6948Expertise: Cheminformatics
Tools: Jupyter notebook, Python, R, Workflows
Expertise: Data Management, Database Development, Semantic Web, Ontology, Knowledge Graph
Teams: ERGA Annotation, Bioinformatics Laboratory for Genomics and Biodiversity (LBGB)
Organizations: Genoscope
https://orcid.org/0000-0002-6621-9908Expertise: Bioinformatics
Tools: Nextflow, Python, R, Genetic analysis, Single Cell analysis
Expertise: Genomics, Metagenomics, NGS, Python, evolution
Tools: Genomics, Python, Snakemake, Transcriptomics
Teams: Cimorgh IT solutions
Organizations: cimorgh IT
Expertise: Bioinformatics, Genomics, Metagenomics, Microbiology, NGS, Python, R, bash, WDL
Tools: Mathematical Modelling, R, WDL
Expertise: Geophysics, Mathematical Modelling, Probabilistic Inversion, Theoretical Seismology
Tools: Python, C++, Mathematical Modelling
Expertise: phylogenomics, phylogenetics, evolution, Microbiology, numerical methods
Hi! I'm Russell.
I'm a microbiologist who uses graph theory and machine learning to study the relationships that bacteria and archaea form with their host organisms, and lately giant viruses and their hosts. Or, I'm a computer scientist who builds software that uses concepts from evolution to extract knowledge about ecology from large datasets. Or, I'm a data scientist who uses Python to explore biological systems. Or, I'm a physicist that went rouge and defected to the squishy side of science. ...
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, Genomics, Metagenomics, Data Management
Tools: CWL, Jupyter notebook, Nextflow, Molecular Biology, Workflows, Microbiology, Transcriptomics, Perl, Python, R
Teams: Not specified
Organizations: Not specified
Expertise: image analysis, Software Engineering, Computer Science
Teams: Applied Computational Biology at IEG/HMGU
Organizations: Helmholtz Zentrum München
https://orcid.org/0000-0003-4796-1661Expertise: Software Engineering, Machine Learning, AI
Tools: Java, Jupyter notebook, Web services, Python
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!
Teams: EU-Openscreen, OME
Organizations: Fraunhofer Institute for Translational Medicine and Pharmacology ITMP
https://orcid.org/0000-0002-1740-8390Expertise: Cheminformatics, Bioinformatics
Teams: Bioinformatics Innovation Lab
Organizations: Pondicherry University
https://orcid.org/0000-0003-4854-8238Expertise: 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)
https://orcid.org/0000-0003-3791-3973Expertise: Bioinformatics, Genomics, algorithm, Machine Learning, Metagenomics, NGS, Computer Science
Tools: Transcriptomics, Genomics, Python, C/C++, Web services, Workflows
Expertise: Bioinformatics
Bioinformatician in Stockholm, Sweden. Lead for nf-core and MultiQC projects.
Teams: IBISBA Workflows
Organizations: Unspecified
Expertise: Bioinformatics
Tools: Workflows, Web services, Python
cfDNA UniFlow is a unified, standardized, and ready-to-use workflow for processing whole genome sequencing (WGS) cfDNA samples from liquid biopsies. It includes essential steps for pre-processing raw cfDNA samples, quality control and reporting. Additionally, several optional utility functions like GC bias correction and estimation of copy number state are included. Finally, we provide specialized methods for extracting coverage derived signals and visualizations comparing cases and controls. ...
Name: KMeans Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: MareNostrum5
KMEans for clustering the housing.csv dataset (https://github.com/sonarsushant/California-House-Price-Prediction/blob/master/housing.csv). This application used dislib-0.9.0
Calculates the Fibonacci series up to a specified length.
Type: COMPSs
Creator: Uploading this Workflow under the guidance of Raül Sirvent.
Submitter: Ashish Bhawel
Name: Dislib Distributed Training - Cache OFF Contact Person: cristian.tatu@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: Minotauro-MN4
PyTorch distributed training of CNN on GPU. Launched using 32 GPUs (16 nodes). Dataset: Imagenet Version dislib-0.9 Version PyTorch 1.7.1+cu101
Average task execution time: 84 seconds
Type: COMPSs
Creators: Cristian Tatu, The Workflows and Distributed Computing Team (https://www.bsc.es/discover-bsc/organisation/scientific-structure/workflows-and-distributed-computing/)
Submitter: Cristian Tatu
Name: Random Forest Contact Person: support-compss@bsc.es Access Level: public License Agreement: Apache2 Platform: COMPSs Machine: MareNostrum4 This is an example of Random Forest algorithm from dislib. To show the usage, the code generates a synthetical input matrix. The results are printed by screen. This application used dislib-0.9.0
Evaluation of Swin Transformer and knowledge transfer for denoising of super-resolution structured illumination microscopy data
In recent years, convolutional neural network (CNN)-based methods have shown remarkable performance in the denoising and reconstruction of super-resolved structured illumination microscopy (SR-SIM) data. Therefore, CNN-based architectures have been the main focus of existing studies. Recently, however, an alternative and highly competitive deep learning architecture, ...
MMV Im2Im Transformation
A generic python package for deep learning based image-to-image transformation in biomedical applications
The main branch will be further developed in order to be able to use the latest state of the art techniques and methods in the future. To reproduce the results of our manuscript, we refer to the branch ...
IDR is based on OMERO and thus all what we show in this notebook can be easily adjusted for use against another OMERO server, e.g. your institutional OMERO server instance.
The main objective of this notebook is to demonstrate how public resources such as the IDR can be used to train your neural network or validate software tools.
The authors of the PLOS Biology paper, "Nessys: A new set of tools for the automated detection of nuclei within intact tissues and dense 3D cultures" published in August ...
Learning objectives
- Read data to analyse from an object store.
- Analyse data in parallel using Dask.
- Show how to use public resources to train neural network.
- Load labels associated to the original data
- Compare results with ground truth.
The authors of the PLOS Biology paper, "Nessys: A new set of tools for the automated detection of nuclei within intact tissues and dense 3D cultures" published in August 2019: https://doi.org/10.1371/journal.pbio.3000388, considered several image ...
Type: Unrecognized workflow type
Creators: Jean-Marie Burel, Petr Walczysko
Submitter: Jean-Marie Burel
Learning Objectives
- How to access genomic resource via its Python API
- How to access image resource via its Python API
- Relate image data to genomic data
Diabetes related genes expressed in pancreas
This notebook looks at the question Which diabetes related genes are expressed in the pancreas? Tissue and disease can be modified.
Steps:
- Query humanmine.org, an integrated database of Homo sapiens genomic data using the intermine API to find the ...
The image is referenced in the paper "NesSys: a novel method for accurate nuclear segmentation in 3D" published August 2019 in PLOS Biology: https://doi.org/10.1371/journal.pbio.3000388 and can be viewed online in the Image Data Resource.
This original image was converted into the Zarr format. The analysis results produced by the authors of the paper were converted into labels and linked to the Zarr file which was placed into a public ...
Type: Unrecognized workflow type
Creators: Jean-Marie Burel, Petr Walczysko
Submitter: Jean-Marie Burel
BatchConvert
A command line tool for converting image data into either of the standard file formats OME-TIFF or OME-Zarr.
The tool wraps the dedicated file converters bfconvert and bioformats2raw to convert into OME-TIFF or OME-Zarr, respectively. The workflow management system NextFlow is used to perform conversion in parallel for batches of images.
The tool also wraps s3 and Aspera clients (go-mc and aspera-cli, respectively). ...