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Contact


Email

ngoonasekera@unimelb.edu.au

Credentials


Position
Bioinformatics Developer- LSCC
Australian Biocommons
Education
PhD
Queensland University of Technology
Bachelors Degree (Honours)
Manchester Metropolitan University
ORCID

0000-0002-3019-2934

Dr Nuwan Goonasekera

Bioinformatics Developer- LSCC
Australian Biocommons

18 Scholarly works
2 Projects

HIGHLIGHTS

  • 2026

    Journal article

    Galaxy for accessible, reproducible, and collaborative data analyses: 2026 update.
    DOI: 10.1093/nar/gkag469
  • 2026

    Journal article

    Right-Sizing Compute Resource Allocations for Bioinformatics Tools with Total Perspective Vortex
    DOI: 10.1007/s42979-026-04947-0
  • 2024

    Journal article

    Galaxy Helm chart: a standardized method for deploying production Galaxy servers
    DOI: 10.1093/bioinformatics/btae486
  • 2024

    Research grants (international)

    Alliance Cloud Connect Pilot
  • 2024

    Journal article

    The Galaxy platform for accessible, reproducible, and collaborative data analyses: 2024 update
    DOI: 10.1093/nar/gkae410
  • 2022

    Conference Proceedings

    Custos Secrets: a Service for Managing User-Provided Resource Credential Secrets for Science Gateways
    DOI: 10.1145/3491418.3535177
  • 2021

    Research Grant

    Extending Galaxy for Large-Scale and Integrative Biomedical Analyses (EOSS3)
Nuwan Goonasekera

RECENT SCHOLARLY WORKS

  • 2022

    Journal article

    The Galaxy platform for accessible, reproducible and collaborative biomedical analyses: 2022 update
    DOI: 10.1093/nar/gkac247
  • 2021

    Journal article

    GalaxyCloudRunner: Enhancing scalable computing for Galaxy
    DOI: 10.1093/bioinformatics/btaa860
  • 2019

    Journal article

    CloudLaunch: Discover and deploy cloud applications
    DOI: 10.1016/j.future.2018.04.037
  • 2018

    Conference Proceedings

    Federated Galaxy: Biomedical Computing at the Frontier
    DOI: 10.1109/CLOUD.2018.00124
  • 2018

    Conference Proceedings

    ICTer 2018 T1) An Introduction to the Galaxy Platform for Computational Biology
    DOI: 10.1109/icter.2018.8615548

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