Machine learning consulting

The Machine Learning Consulting service supports researchers in the planning and development of machine learning projects using proteomics and corresponding clinical data. From discussing study requirements (e.g. what data are needed and how many samples/data points are sufficient), to selecting appropriate algorithms, interpreting model outputs, and communicating results, we guide users through all key stages of the project. In addition to consulting, we also offer to perform machine learning analyses on request.

Key benefits
  • End-to-end guidance for machine learning projects in proteomics and clinical research
  • Support in selecting suitable methods and avoiding common pitfalls (e.g. data leakage)
  • Focus on interpretability, validation, and robust performance assessment
  • Option to receive hands-on analysis support in addition to consulting
  • Assistance with documentation and publication writing for the machine learning components
Applications
  • Data assessment: anomaly detection, exploratory data analysis, and quality checks
  • Model development: predictive modeling such as classification and clustering
  • Data leakage prevention and detection: support across all modeling phases
  • Interpretability and explainability: e.g. SHAP-based explanations and feature attribution
  • Validation and robustness: cross-validation strategies, robustness checks, and performance assessment
  • Evaluation metrics: e.g. Matthews Correlation Coefficient (MCC), AUROC, and additional fit-for-purpose metrics
  • Scientific communication: technical documentation and support for writing ML-related methods/results sections
Intended use

This service is intended for researchers working with proteomics data and clinical or biomedical datasets who want to apply machine learning in a rigorous, reproducible, and interpretable way. It is particularly suited for users who need expert guidance on study planning, model selection, prevention of methodological pitfalls, and robust evaluation of model performance.

Website

This email address is being protected from spambots. You need JavaScript enabled to view it.

Funding: Service provision and maintenance funded by de.NBI.