The Advanced Compute and Data Core (ACDC) enables the FAIR (Findable, Accessible, Interoperable and Reusable), integration, analysis and sharing of omics and imaging research across the Amsterdam UMC. We are developing an integrated platform of data services and High Performance Compute (HPC) resources, to facilitate the management, analysis and reuse of research assets.
In collaboration with the imaging, flow cytometry, genomics, proteomics and metabolomics core facilities, and drawing on our experiences in national and international FAIR data initiatives, we are enabling data reuse and knowledge discovery and developing new approaches to the integrated analysis of bioimaging and omics data.
Daoud L.S. Sie, PhD
Lead High Performance Compute Expert
ORCID: 0000-0001-6762-2582 / Google Scholar
Daoud obtained his PhD in the field of Cancer Genomics, where he developed bioinformatics tools in the department of Pathology. At the same time he coordinated a research activities in the Tumor Genome Analysis Core. After finishing his PhD, he started as the head of bioinformatics in the department of Human Genetics and as a scientific consultant for the Core Facility Genomics. Recently, Daoud has developed a plan in collaboration with all the Omics & Bioimaging core facilities, which resulted in the establishment of the Advanced Compute & Data Core.
Katy J. Wolstencroft, PhD
Lead Data Management Expert
ORCID: 0000-0002-1279-5133 / Google Scholar
Katy obtained her PhD in bioinformatics from the University of Manchester, where she was also a post-doc and research fellow. In 2013, she became an Assistant Professor at the Leiden Institute of Advanced Computer Science (LIACS), where she set up her own research group, Life Science Semantics, to study data and knowledge integration for biomedical data science. In November 2024, she became an Associate Professor at the Amsterdam UMC to lead the Data Hub developments in the Advanced Compute & Data Core.
Katy was involved in defining the FAIR Principles. She works on methods and infrastructure for developing and exploiting FAIR data and enabling reproducible research. In addition to ACDC, she leads the Data and Analysis node of the NL-Bioimaging National Research Infrastructure.
Karen A. Sap, PhD
Data Steward
ORCID: 0000-0002-5806-2103 / Google Scholar
Karen is a Data Steward for the ACDC team with a strong background in both
wet lab research and data management. Holding a Bachelor’s in Biochemistry, a
Master’s in Cell Biology, and a PhD in Biochemistry, Karen has extensive
experience in molecular biology, biochemistry, flow cytometry, microscopy, and
mass spectrometry.
During a PhD at the Proteomics Core Facility of Erasmus MC, Karen developed
and applied quantitative mass spectrometry methods to analyze the ubiquitin
landscape, working with large-scale proteomics datasets. In a subsequent
postdoctoral role at the lab of Eric Reits at AUMC, these techniques were used
to study the role of ubiquitin in Huntington’s disease, further strengthening
expertise in handling and interpreting big datasets.
In the current role as a Data Steward, Karen is focused on implementing an
iRODS-based data management system to automate the handling of multi-omics
and imaging data for AUMC core facilities. Additionally, Karen develops data
solutions, such as automating metadata structuring and validation, to facilitate
submissions to public repositories and furthermore assists researchers in
drafting data management plans.
With expertise in both experimental research and large-scale data management,
Karen plays a key role in bridging scientific and data-driven approaches to
support research at AUMC.
Alberto Miranda Bedate, PhD
Data Steward
ORCID: 0000-0003-2623-2857 / Google Scholar
After obtaining his PhD in molecular biology in Spain, he developed his postdoctoral career in biomedical sciences in the Netherlands. As next-generation sequencing became mainstream, he specialized in bioinformatics and multi-omics technologies. More recently, he was attracted by the (big)data-driven solutions developed in biotech companies. More concretely, he was actively involved in building knowledge bases of gene/protein (meta)data and in implementing Python solutions for AI-based technologies, such as AI agents for fetching gene, genome sequences, and metadata from several mainstream APIs (e.g., Uniprot, EnsEMBL). All these experiences made him aware of the importance of FAIR data for research (r)evolution, and he is looking forward to tackling the data challenges at the Amsterdam UMC.
Bilgehan C. Nevruz
Software Engineer, HPC Specialist
After earning a bachelor’s degree in bioengineering in Turkey, he started his career in bioinformatics, specializing in next-generation sequencing (NGS) and multi-omics technologies. He developed WES (whole exome sequencing), RNA-Seq pipelines and contributed to various research projects. Over time, he became increasingly interested in workflow development and software engineering, particularly in automation and scalable data solutions. He is now looking forward to solving HPC and software-related challenges at Amsterdam UMC.
Alex A. Henneman, PhD
Software Engineer, HPC Specialist
ORCID: 0000-0002-3746-4410
Dr. Alex Henneman received his Ph.D. degree in Theoretical High Eenergy Physics from the Vrije Universiteit in 2005. Subsequently, he worked as a bioinformatician at the Center for Proteomics and Metabolomics of the Leiden University Medical Center. In 2016, he joined the OPL to work on a collaborative project with the Translational Gastrointestinal Oncology group (Dr. Beatriz Carvalho and Prof. Gerrit Meijer) at the Dutch Cancer Institute (NKI), sponsored by a joint Dutch Cancer Society (KWF) project entitled “Signaling pathways involved in colorectal adenoma-to-carcinoma progression”. To this end, he focusses on (integrative) phosphoproteomics data analysis strategies for biomarker discovery.