The main aim of the MelanoBase project is a large-scale automatic extraction of actionable information from the biomedical literature and its integration with existing structured knowledge (life science databases). The innovative outcome of this strategy is to provide users  (basic and clinical researchers) with formats that can be more easily queried, and automatically processed, with the purpose of increasing the efficiency of biology research. The specific use-case scenario of melanoma disease has been selected for the histopathological complexity of these lesions, and to provide solutions for the unmet need of separating true drivers of this disease from a myriad of (epi)genetic inconsequential byproducts accumulated during melanoma genesis. The project will pursue a literature-wide and disease-centric approach which sets it apart from comparable projects worldwide. Moreover, close collaborations with experts in the field will streamline validation efforts in clinically-relevant specimens.

Conceptual index of the biomedical scientific literature with named entities, relations, and pointers to textual evidence
MelanoBase's vision: a conceptual index of the entire biomedical scientific literature, containing references to entities (eg. diseases, genes/proteins, chemicals) and relations as well as pointers to textual evidence.


Main Goals

  • integrate all available knowledge about melanoma, with particular emphasis on hard-to-diagnose lesions and on mechanisms of resistance to clinically approved treatments and compounds in experimental testing
  • enable integration of the unstructured knowledge available in the literature with the structured knowledge deposited in life sciences databases
  • include additional sources such as clinical trial reports, systematic reviews (Cochrane), and prescription drug information (second stage)
  • ultimately, accelerate gene discovery and drug target validation in the area of melanoma

The results of the MelanoBase project will be integrated  within the Melanoma Molecular Map repository and experimentally relevant information will be validated by well-known experts in the field.

Project head:

Dr. Fabio Rinaldi


Lenz Furrer

Main collaborations:

Dr. Raul Rodriguez-Esteban, Roche, Switzerland
Dr. María S. Soengas, CNIO, Spain
Dr. Simone Mocellin, University of Padova, Italy

The project is funded by the Swiss National Science Foundation (SNF) and runs 2016–2018.