Integrative Computational Network Biology (ICONBI)

Los datos ómicos, heterogéneos, interconectados, a nivel de sistemas, están cada vez más disponibles y se aplican en la medicina de precisión. Buscamos estratificar mejor a los pacientes en grupos de riesgo, descubrir nuevos biomarcadores para enfermedades, personalizar tratamientos médicos y reutilizar medicamentos conocidos para...

Prof. Dr. Natasa Przulj has made outstanding contributions to the field of network science. She is the inventor of graphlets, a methodology now utilized in many algorithms. She initiated extraction of biomedical knowledge from the wiring patterns (topology) of complex and large molecular (omic) networks. Her recent work includes designing machine learning methods, mostly...

This PoC project aims to pave the road to commercialize a comprehensive data analytics platform enabling data-driven biomedical innovation and precision medicine. The platform is specifically designed to efficiently fuse and mine heterogeneous omic data, including genomes, epigenomes, proteomes, metabolomes, patient clinical profiles, drugs and their chemical similarities,...

Due to technological advances in experimental biology, we now have an astounding amount of various molecular and clinical data describing different aspects of the functioning of the cells. These complex big data carry biomedical information that is currently hidden from us within their large sizes and complexities. Hence, some of the foremost computational challenges that the...