Translational Bioinformatics Laboratory (TBL)
Department of Medicine and Surgery · University of Milano-Bicocca

Computational oncology · Mutational processes · Multi-omics

Translational Bioinformatics Laboratory (TBL)

We develop advanced computational and statistical methods to study cancer evolution, mutational processes and multi-omics heterogeneity, bridging fundamental biology with clinical applications.

The lab is based at the Department of Medicine and Surgery, University of Milano-Bicocca, and works at the intersection of computer science, statistics, genomics and oncology.

Research pillars

Cancer evolution & clonal dynamics

Models and algorithms to reconstruct tumour progression from single-cell, multi-region and longitudinal sequencing data.

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Mutational signatures & genomic processes

High-resolution characterization of mutational processes shaping tumour genomes and their association with prognosis and therapy.

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Multi-omics integration & stratification

Machine learning frameworks to integrate genomic, transcriptomic and clinical data and identify clinically relevant tumour subtypes.

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Translational bioinformatics

Collaborations with clinicians in oncology and haematology to derive biomarkers, risk models and decision support tools directly from patient data.

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Latest news & events

  • May 2026 – ProgEvo / IPSS-M-Evo published in NEJM Evidence
    The lab introduces an evolution-informed prognostic score for myelodysplastic syndromes, with a linked editorial highlighting the move from static mutation lists to dynamic clonal-evolution risk.
    Read more in News →
  • 2026 – My First AIRC Grant (MFAG 2025)
    Daniele Ramazzotti is awarded a My First AIRC Grant (MFAG 2025) by Fondazione AIRC for Cancer Research.
    Read more in News →
  • 2025 – EvoClin wins the Premio Nazionale Innovazione (PNI) 2025
    EvoClin, a university spin-off project under development, wins the PNI 2025 award in the Life Sciences & MedTech category.
    Read more in News →
  • 2025 – NRF2-based signature across cancers
    The ASTUTE framework identifies an NRF2 expression signature with prognostic value across multiple tumour types, in collaboration with clinical and experimental groups at UniMiB and San Gerardo.
    Read more in News →

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Highlights

Publications

70+ peer-reviewed publications across NEJM Evidence, Nature, Nature Cancer, Nature Communications, Nucleic Acids Research, Cancer Discovery, iScience and others.

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Software

Open-source tools including ASCETIC, RESOLVE, SparseSignatures, CIMLR, SIMLR, VERSO, TRONCO, LACE and more, widely used in cancer genomics.

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Funding & recognition

PI or co-PI on competitive grants including PRIN 2022, PRIN PNRR, Ricerca Finalizzata, Bicocca University Starting Grant, BRCA Foundation Young Investigator Award and ICI Discovery Grant.

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