Our Mission

The mission of our Division and Center is to pursue excellence in scientific research and education on fundamental questions in life science with informatics and systems approaches, on theoretical and methodological questions therein for information science and technology, on the informatics mechanism of life systems, and on the engineering of molecular regulatory systems.

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  • Tsinghua Distinguished Synbio Seminar Series

    Tsinghua Distinguished Synbio Seminar Series

    Speaker Timothy K. Lu Assistant Professor of Biological Engineering and Electrical Engineering Synthetic Biology Group, MIT Title: Synthetic Analog and Digital Platforms for Scalable Biological Computation Location: FIT 1-315 Time: […]

  • A Bayesian View of Sliced Inverse Regression with Interaction Detection

    A Bayesian View of Sliced Inverse Regression with Interaction Detection

    Previously we have proposed a Bayesian partition model for detecting interactive variables in a classification setting with discrete covariates. This framework takes advantage of the structure of the naïve Bayes classifier and introduces latent indicator variables for selecting variables and interactions. In our effort to extend the methods to continuous covariates, we found interesting connections with semi-parametric index models and the Sliced Inverse Regression method. In index models, the response is influenced by the covariates through an unknown function of several linear combinations of the predictors. Our finding of the Bayesian formulation of such models enabled us to propose a set of new models and methods that can effectively discover second-order effects and interactions among the covariates. A two-stage stepwise procedure based on likelihood ratio test is developed to select relevant predictors and a Bayesian model with dynamic slicing scheme is derived. The performance of the proposed procedure in comparison with some existing method is demonstrated through simulation studies.

  • Current Topics in Genomics and Epigenomics

  • Group Photo 2013

  • Group Photo 2012