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Emerging multifactorial diseases usually bear loosely defined etiology and pathogenesis mechanisms. So far, it has been extremely difficult for doctors to provide sensitive and specific diagnosis and prognosis on these diseases. To tackle this increasing serious global health problem, Dr. Ling and his team are striving to leverage high throughput biological data set, which can potentially alter how we view and define these diseases, and more importantly, the efficiency and effectiveness in treating them.
His lab employs a comprehensive multi-“omics” approach, which is to integrate big datasets of genomics, metabolomics, and proteomics to define the molecular “portrait” and relative health risk against the population baseline. The team also takes on the population risk analytics approach, which integrates both structured and unstructured clinical information with the aim to risk stratify the population to allow preventive or targeted care.
Data-driven healthcare is defined as usage of big data, representing the collective learning in treating hundreds of millions of patients, to provide the best and most personalized care. Big-Data based BI/AI (Business Intelligence/Artificial Intelligence) in health care is starting to improve practice quality and outcomes, and reduce practice-induced adverse outcomes.
Following his PhD under Academy member Dr. Michael Grunstein from UCLA, Dr. Ling did a post-doc in molecular immunology under Dr. Alan Krensky at Stanford Medicine and simultaneously trained in computer science. Dr. Ling’s investigative interests are in translation medicine that bridge molecular biology and biomedical computation. Dr. Ling brings a great depth of experience and demonstrated success in using his computational skills to create both platforms and products with obvious translational utility. During his tenure at Stanford, Dr. Ling has been instrumental in creating the computational infrastructure to support diagnostic biomarker discovery and more recently in providing mechanism of disease insight. Dr. Ling has established a number of fertile collaborations both within the Stanford community as well as with other leading scientists in academia and industry.
Following his PhD under Academy member Dr. Michael Grunstein from UCLA, Dr. Ling did a post-doc in molecular immunology under Dr. Alan Krensky at Stanford Medicine and simultaneously trained in computer science. Dr. Ling’s investigative interests are in translation medicine that bridge molecular biology and biomedical computation. Dr. Ling brings a great depth of experience and demonstrated success in using his computational skills to create both platforms and products with obvious translational utility. During his tenure at Stanford, Dr. Ling has been instrumental in creating the computational infrastructure to support diagnostic biomarker discovery and more recently in providing mechanism of disease insight. Dr. Ling has established a number of fertile collaborations both within the Stanford community as well as with other leading scientists in academia and industry.
Agenda
- Lunch
- Presentation and Discussion
Bruce Ling
Bruce Ling
Professor, Principle InvestigatorFollowing his PhD under Academy member Dr. Michael Grunstein from UCLA, Dr. Ling did a post-doc in molecular immunology under Dr. Alan Krensky at Stanford Medicine and simultaneously trained in computer science. Dr. Ling’s investigative interests are in translation medicine that bridge molecular biology and biomedical computation. Dr. Ling brings a great depth of experience and demonstrated success in using his computational skills to create both platforms and products with obvious translational utility. During his tenure at Stanford, Dr. Ling has been instrumental in creating the computational infrastructure to support diagnostic biomarker discovery and more recently in providing mechanism of disease insight. Dr. Ling has established a number of fertile collaborations both within the Stanford community as well as with other leading scientists in academia and industry.
