A principled learning approach has become indispensable for extracting knowledge from large arrays of numbers. In the case of computational molecular medicine, this entails revealing and exploiting disease-related information implicitly stored …

Students develop new solutions in personalized medicine by building computational models of the molecular biology, physiology, and anatomy of human health and disease.

The Data Science in Biomedicine MS provides training in Data Science, Machine Learning, Statistics, Data Mining, Algorithms, and Analytics with applications to Genomics, Electronic Health Records, and Medical Images.

Computational Molecular Medicine harnesses the enormous amount of disease-relevant data produced by next-generation sequencing, microarray and proteomic experiments of large patient cohorts, using statistical models to identify the drivers of disease and the susceptible links in disease networks.

The Institute for Computational Medicine (ICM) uses powerful computational tools to transform the practice of medicine. Learn more »

Our goal is an improved understanding of the genetic basis of gene regulation and its implication in diseases. To this end, we employ statistical modeling of 'omic data and work in close collaboration with experimentalists.

We discuss advances in computational medicine, with specific examples in the fields of cancer, diabetes, cardiology, and neurology. Advances in translating these computational methods to the clinic are described, as well as challenges in applying models for improving patient health.

Computational Molecular Medicine harnesses the enormous amount of disease-relevant data produced by next-generation sequencing, microarray and proteomic experiments of large patient cohorts, using statistical models to identify the drivers of disease and the susceptible links in disease networks.

2020年12月6日 · The domain of computational biomedicine is a new and burgeoning one. Its areas of concern cover all scales of human biology and pathology from the genomic to the whole human and beyond, including epidemiology and population health.

Computational Molecular Medicine harnesses the enormous amount of disease-relevant data produced by next-generation sequencing, microarray and proteomic experiments of large patient cohorts, using statistical models to identify the drivers of disease and the susceptible links in disease networks.