Client: CDTI (Centro para el Desarrollo Tecnológico Industrial)
Solution: Big Data and machine learning
- Design and construction of a Big Data system for storing and later analysis of large data sets generated in proteomic studies.
- Design and implementation of different tools that will allow the manipulation and exchange of information between systems and equipment.
- Definition, optimization and indexing of the physical architecture of DataMart.
- Standard solution development and reporting.
- Machine learning for the identification of the peptic print.
Within the framework of the Feder Interconecta programmes, the partnership formed by Altia, AMSlab and SolidQ, together with two research groups of Instituto de Investigación Biomédica de A Coruña (Inibic), have jointly developed the DIPROA project with the aim of carrying out an early diagnosis of osteoarthritis, based on the protein footprint of this disease.
Therefore, an integrated tool was developed for classifying and diagnosing patients, capable of automatically processing all clinical and genomic information.