Develop new quantitative modeling methods and advanced computational approaches to advance understanding of biological systems and improve human health.

It is widely anticipated that quantitative modeling, advanced computing and data science will transform the biomedical research enterprise and practice of medicine in the coming decades as fundamentally as biochemistry and molecular biology transformed it during the past century. With leading researchers from seven institutions, the Quantitative & Computational Biosciences graduate program brings together the resources of the Texas Medical Center -- the world's largest complex of biomedical research institutions and hospitals, Rice University and neighboring institutions to discover new biomedical knowledge and improve human health. 

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Faculty

Our full-time faculty includes basic and clinical scientists from seven institutions -- Baylor College of Medicine, Methodist Research Institute, Rice University, University of Houston, University of Texas Health Science Center, University of Texas Medical Branch at Galveston and University of Texas MD Anderson Cancer Center.

Diverse Backgrounds, Diverse Research Interests, Diverse Career Goals (372x158)

Where Will Your Ph.D. Take You

From day one we encourage you to think deeply about your career choices. Wherever your ambition leads, you will receive the support you need to follow a path well worn by our alumni who have built successful careers across diverse endeavors. 

QCB News

Gene Editing Just Got Easier

An international team of researchers has made CRISPR technology more accessible and standardized by simplifying its complex implementation. The simpler, faster CRISPR, which is presented in the journal Nature Communications, offers a broad platform for off-the-shelf genome engineering that may lower the barrier of entry for this powerful technology.

credit: Chiu lab.
Faster Analysis of Cryo-Electron Tomography Images

Researchers use cryo-electron tomography to visualize macromolecules frozen in action and details of structures inside of cells. Looking to increase the efficiency of the time-consuming process of annotation, BCM researchers developed an automated method that requires less human participation.

From the Labs

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