Teaching & training

Bachelor & single-cycle degree teaching

Within the Department of Medicine and Surgery, Daniele Ramazzotti is involved in teaching informatics and information processing to students in health-related degree programmes, including Medicine and Surgery, Odontology, Dental Hygiene and Radiology.

• Basis of Signal Processing – 2 CFU
  Bachelor Degree – Tecniche di Radiologia Medica, per Immagini e Radioterapia [I0303D], 1st year (ING-INF/06)
  Course on the fundamental principles of signal processing with applications to medical imaging: time and frequency domain representations, transforms, sampling and quantisation, filtering and introduction to medical imaging technologies.
  Syllabus (e-learning, a.a. 2025–2026) →
  Course page (e-learning, a.a. 2025–2026) →
• Informatics proficiency (Idoneità Informatica – Livello Base e Avanzato)
  School of Medicine and Surgery – Health Profession bachelor degrees, Medicine and Surgery, Dentistry
  The department is required to verify students’ informatics skills at basic and advanced level. Informatics proficiency can be obtained via recognised certifications, previous careers or a dedicated examination organised in the computer laboratories in Monza. Daniele Ramazzotti serves as the responsible instructor for these activities.
  Department page – Informatics proficiency →
  Idoneità Informatica – Base e Avanzato (e-learning) →
• Information Processing Systems – 1 CFU
  Bachelor Degree – Igiene Dentale [I0301D], 2nd year (ING-INF/06)
  Course providing the foundations for understanding the architecture of information processing systems, software and telecommunications networks, with a focus on data storage, coding and web information systems in healthcare.
  Syllabus (e-learning, a.a. 2025–2026) →
  Course page (e-learning, a.a. 2025–2026) →

Master’s degree programmes

At the master’s level, Daniele Ramazzotti teaches in the Master’s degree in Medical Biotechnology (Biotecnologie Mediche, LM-9), with a focus on quantitative and computational methods for analysing biomedical and omics data.

• Data Analysis – 6 CFU
  Master Degree – Biotecnologie Mediche [F0902D - F0901D], 1st year
  Integrated course composed of two teaching units: Biostatistics and Bioinformatics. Daniele Ramazzotti teaches the Bioinformatics module (INF/01), focusing on computational methods for the analysis of molecular data: sequencing technologies (NGS), biological sequence databases, genome reconstruction and annotation, alignment algorithms, phylogeny reconstruction and transcriptome analysis.
  Bioinformatics module – syllabus (e-learning, a.a. 2025–2026) →
  Bioinformatics module – course page (e-learning, a.a. 2025–2026) →

TBL contributes to the training of PhD students, clinicians and professionals through specialised courses and modules, both within UniMiB doctoral programmes and advanced training initiatives.

• Image Processing with ImageJ
  PhD School – Translational and Molecular Medicine (DIMET)
  Postgraduate course on practical image processing using ImageJ, with applications to biomedical and microscopy data. The teaching team includes Mario Mauri and Daniele Ramazzotti as instructors.
  Course page →
• Omics Data elaboration
  QOmics: quantitative methods for Omics Data – Bicocca Academy advanced master
  Course on computational and quantitative methods for the analysis of high-throughput omics data, within the QOmics advanced training programme. Daniele Ramazzotti is one of the teachers together with colleagues from the QOmics faculty.
  Omics Data elaboration (e-learning) →

In addition to formal courses, TBL members regularly participate in PhD seminars and doctoral teaching activities covering:

• cancer evolution and clonal dynamics;
• mutational signatures and genomic processes;
• multi-omics integration and patient stratification;
• statistical and machine learning methods for biomedical data.

In addition to degree and PhD courses, Daniele Ramazzotti contributes to the teaching activities of several medical Schools of Specialization within the Department of Medicine and Surgery, mainly on topics related to biostatistics, bioinformatics and data analysis for clinical research.

• Approfondimenti di Statistica Medica per la Ricerca Clinica – 1 CFU
  Department of Medicine and Surgery
  Elective course focused on advanced topics in medical statistics for clinical research, including study design, statistical modelling and interpretation of results in translational and clinical studies.
• Schools of Specialization in Medical Genetics and Medical Oncology – teaching module 2 CFU
  Postgraduate medical training
  Mutuated teaching activities focused on data analysis in R, covering data manipulation, exploratory analysis, visualization, and introductory workflows for handling clinical and molecular datasets relevant to genetics and oncology.
• Schools of Specialization in Medicine – teaching module 2 CFU
  Postgraduate medical training
  Lectures and practical sessions on basic and applied data analysis with R, aimed at residents in internal medicine and related disciplines.
• School of Specialization in Oral Surgery – 2 hours
  Postgraduate dental surgical training
  Short module introducing principles of data management and quantitative analysis for surgical and diagnostic dentistry.

Beyond UniMiB, Daniele Ramazzotti has contributed to international teaching initiatives at the interface of data science and medicine.

• Data Pre-processing – MIT Critical Data / MITx HST.953x
  Daniele Ramazzotti co-developed teaching materials on data pre-processing for electronic health records as part of the MIT Critical Data initiative and the online course HST.953x Secondary Analysis of Electronic Health Records, including videos and modules hosted on the MIT Open Learning Library.
  MITx HST.953x – Secondary Analysis of Electronic Health Records →

These activities complement the laboratory’s local teaching by providing an international perspective on clinical data science and large-scale biomedical datasets.

The Translational Bioinformatics Laboratory supervises MSc theses, PhD projects and postdoctoral research in translational bioinformatics and cancer data science.

Typical thesis and project topics include:

• computational models of cancer evolution and clonal dynamics;
• mutational signature analysis and characterization of genomic processes;
• integration of genomic, transcriptomic and clinical data (multi-omics);
• methods for single-cell sequencing and tumour heterogeneity;
• algorithm development and software tools for translational oncology.

Prospective students interested in joining the lab for a thesis or research project can find more information in the Join Us section or by contacting Daniele Ramazzotti directly via email.

Members of the TBL regularly give invited seminars and lectures in internal seminars of the Department of Medicine and Surgery, national schools and international workshops on topics such as:

• evolutionary trajectories in cancer and treatment resistance;
• mutational processes in human tumours and in viral evolution (e.g., SARS-CoV-2);
• applications of machine learning and statistics to clinical and omics data;
• best practices for reproducible research and data management in translational medicine.

Events related to the laboratory’s activities are announced in the News section.