Alexander Loboda

Standard Bio (Norway)

Papers

1

Total Citations

2

H-Index

1

About

Dr. Alexander Loboda is a leading computational biologist whose research bridges multi-modal imaging, cancer immunology, and large-scale data integration. His most prominent work, "Multi-modal image analysis for large-scale cancer tissue studies within IMMUcan" (2025, 2 citations), exemplifies his role in the IMMUcan consortium, where he develops cutting-edge pipelines to analyze multiplexed imaging data from thousands of patients. By integrating diverse imaging modalities, Dr. Loboda enables detailed characterization of the tumor microenvironment (TME), linking cellular architecture and immune cell distributions to patient prognosis. His contributions are pivotal for translating complex spatial biology into clinically actionable insights, advancing precision oncology. Though early in its citation trajectory, this work has already garnered attention for its methodological rigor and scalability. Dr. Loboda’s research empowers the cancer community to harness large-scale, multi-modal datasets, setting new standards for immunoprofiling and biomarker discovery. His achievements underscore a commitment to open science and collaborative infrastructure, making him a key figure in the future of computational pathology and TME analysis.

Research Focus

Key Achievements

1
H-Index
1
Papers
2
Total Citations
2
Avg Citations/Paper
🏆 Most Cited Paper
Multi-modal image analysis for large-scale cancer tissue studies within IMMUcan
2 citations · 2025
📈 Most Prolific Year: 2025 (1 Papers)
🤝 Key Collaborators: 22
🏛 Institutions: Standard Bio (Norway)

Top Papers

  1. 1

Key Collaborators

Contact & Links

Available for collaboration
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