PatientProfiler: A network-based approach to personalized medicine

ABSTRACT: Deciphering the mechanisms underlying reprogramming in cancer cells remains a crucial challenge in systems oncology, as it is key to improving patient diagnosis and treatment. For this reason, comprehensive and patient-specific multi-omic characterization of tumor specimens has become increasingly common in clinical practice. The main shortcoming is the absence of robust computational frameworks to integrate and interpret the available multi-dimensional data, to drive translational solutions. To fill this gap, we developed PatientProfiler, a computational workflow that leverages causal interaction data to address how the genetic and molecular background of individual patients contributes in establishing a malignant phenotype. PatientProfiler allows multi-omic data analysis and standardizat

SUBMITTER: Veronica Lombardi 

PROVIDER: S-SCDT-10_1038-S44320-025-00160-Y | biostudies-other |

REPOSITORIES: biostudies-other