Discover what makes SOPHiA DDM™ effective at calling mtDNA variants from exome sequencing data, and see for yourself how in a single workflow, the SOPHiA DDM™️ Platform complemented by Alamut™️ Visual Plus can be used to identify and interpret variants in mtDNA alongside SNVs, Indels, and CNVs in nuclear DNA.
Watch our poster spotlight interview, hosting Dr.Gardenia Vargas from Hospital del Mar in Barcelona, Spain discussing the poster presentation at
Discover how we collaborated with the UroCCR network to develop a machine learning model that outperformed the predictive performance of
Discover how a deep learning algorithm, GIInger™, leverages low-coverage sequencing data to identify homologous recombination deficiency (HRD)-induced genomic instability.
We’re often asked how we avoid overfitting when developing predictive machine learning models for clinical research. This technical note explains
Capturing the complexity of human health and disease through machine learning analysis of multimodal data has the potential to drive
Liquid biopsy is revolutionizing precision oncology with a non-invasive approach to tumor profiling. In this blog, we explore its clinical
Streamlined workflow for Chronic Lymphocytic Leukemia study
Despite the advantages of cascade testing, it is a vastly underused cancer prevention strategy. What are the barriers and facilitators
Companion Diagnostics (CDx) are important tools in the practice and application of precision medicine. This introductory blog provides an overview
Explore the realm of precision medicine as we define its significance, uncover current gaps, and shed light on key areas
Deep learning-based approaches to genomic instability assessment can help overcome the limitations of current methods and maximize insights from tumor
In this Spotlight session, Dr.Elena Repetti, Chief of Medical Genetics of TomaLab in Italy shares with us TomaLab’s mission in
