GRHECO-Xen

This research group has focused on the application of advanced information technologies in the field of oncohematologic tumors. These approaches, reflected in the diversity of our investigations, have centered on the following main objectives: Identification of driver genes in oncogenesis and tumor progression in hematologic neoplasms. Identification of recurrently altered signaling pathways in the genome of hematologic tumors. Development of prognostic machine learning models in different types of oncohematologic neoplasms based on clinical and molecular information. Development of predictive models of drug response or drug combinations based on the integration of molecular and clinical variables. Research Lines Development of new prognostic models based on data from national and international collaborative groups. Standardization of clinical and molecular models to improve risk stratification in patients with hematologic neoplasms, particularly lymphomas, myelomas, and myeloid neoplasms. Development of new scores to predict drug response within clinical trials. Creation of new computer vision systems to infer prognostic patterns based on deep neural networks and transfer learning. Optimization of preclinical drug development using computational tools, including machine learning models.