Big Data Approaches in Health, Disease and Treatment Trajectories
Large-scale data generation, including whole-genome sequencing, transcriptomics, proteomics, metabolomics, microbiome, immunoprofiling, mass cytometry and imaging, is rapidly becoming more accessible in clinical setups. Methods to integrate and infer from data are evolving, and big data approaches show promise in learning the attributes of individual patients that are relevant for subgrouping cohorts and addressing individu alized therapies. Methods to predict disease progression and treatment outcomes – efficacy and toxicity – should ideally incorporate longitudinal large-scale patient data of mixed types, electronic health records and registries and prior biological knowledge from literature and biological model systems. There is a need for further development of methods, prototyping on diseases with detailed phenotyping, education and communication to attain clinical credibility.
The Symposium will explore ideas, emerging methods and case stories in data integration, systems biology, statistical and machine learning as well as Bayesian methods that offer opportunities to benefit from the wealth of emerging patient and health-related data.
Marylyn Ritchie, Pennsylvania State University, United States
Jason H. Moore, Perelman School of Medicine, University of Pennsylvania, United States
Andrea Califano, Columbia University, United States
Chloé-Agathe Azencott, Mines ParisTech, Institut Curie and INSERM, France
Laurent Gautier, Verily Life Sciences, Boston, United States
Who can attend
The symposium is open to participants of all career levels from student to professor.
All attendants are encouraged to bring a poster for the poster session within the following categories:
Integrative Omics and post-GWAS strategies
Artificial intelligence, Prior knowledge and Big data approaches
Implementing Big Data in clinical contexts
Posters will be exhibited during the symposium and discussed during a poster session.
If you wish to bring a poster, you must select participation with poster on the registration site.