Katarzyna Kamieniecka

Katarzyna is the Lead Data Stewardship Trainer for the ELIXIR-UK DaSH project based at the University of Bradford. She is also working towards a PhD in Computational and Data-Driven Science, and has developed a collection of freely available Galaxy tools.

As a UK Node Mentor, her main focus is on the  Galaxy Training Network (GTN), The Carpentries and pedagogical best practices.

Background

I am the Lead Data Stewardship Trainer at The University of Bradford, ELIXIR-UK, working in the field of Data Management and Stewardship in the life sciences. This role gave me an opportunity to get involved in national and international focus groups (ELIXIR, The Carpentries, Galaxy Training Network, nf-core, Northern BUG) with the aim to develop and provide bioinformatics and medical informatics training for clinical fellows and research staff. My background in computational methods and training strongly focuses on robustness and reproducibility.

With an MPhil in Biosciences and an ongoing PhD at the Computational and Data-Driven Science cluster at the University of Bradford. I got involved in skin biomarkers studies and have developed a collection of freely available Galaxy tools, combining analytical methods into a range of convenient analysis pipelines with a graphical user-friendly interface and training [1].

In parallel, I’ve worked for the CRUK MI Cancer Biomarker Centre as a Senior Computational Biologist, developing novel methods and Nextflow pipelines for a better understanding of genomic alterations in cancer derived from patient tumours and liquid biopsies [2]. I was also responsible there for the development and delivery of a series of bioinformatics-focused workshops for the researchers and community.

Throughout all my experiences, with tools and pipeline development supported by networking and community engagement, I turned intensely toward research data management and training delivery.

  • 22 June 2023
    | News

    ELIXIR-UK Fellow launches Galaxy FAIR Training

    Katarzyna Kamieniecka, a member of the ELIXIR-UK Fellowship Programme, has just launched a new series of Galaxy Training Materials. She is aiming to improve FAIR data management in the life […]
  • ELIXIR-UKFellowship
    Data Stewardship Training Fellowship
  • ELIXIR EuropePlatform
    Training Platform
  • Contributing
    A logo of the Galaxy Training Network
    Galaxy Training Network (GTN)

  • 18 June 2024
    | Short course

    FAIR data management in single-cell analysis

    What will you learn? This course will introduce the Galaxy Platform, covering the basic functionality for single-cell data processing. It will include an overview of various common single-cell datatypes used […]
  • 6 June 2024
    | Workshop

    Introduction to data management for peatland research and monitoring

    What will you learn? This workshop will introduce FAIR (Findable, Accessible, Interoperable and Reusable) data management, research data lifecycle and the importance of creating a data management plan for peatland […]
  • 17 May 2024
    | Short course

    Making clinical datasets FAIR

    What will you learn? The life science community is generally very good at sharing omics data on platforms such as GEO and ArrayExpress.  However, the metadata and clinical data associated […]
  • 25 April 2024
    | Short course

    REMBI – Recommended Metadata for Biological Images

    What will you learn? Navigating the intricacies of making your bioimage data FAIR (Findable, Accessible, Interoperable, and Reusable) can seem overwhelming. This session offers strategies for effectively sharing your data […]
  • 11 April 2024
    | Short course

    Data management in Medicinal Chemistry

    What will you learn? The development of medicinal chemistry is advancing very rapidly. Big pharmaceutical companies, research institutes and universities are working on ground-breaking solutions to help patients combat all […]
  • 20 May 2024
    | Workshop

    Intermediate Software Development

    This course aims to teach a core set of established, intermediate-level software development skills and best practices for working as part of a team in a research environment using Python […]