Computational Biology & Bioinformatics

PHD in Computational Biology & Bioinformatics

Program Principles & Goals

The Ph.D. Program in Computational Biology & Bioinformatics (CBB) is an integrative, multi-disciplinary training program that encompasses biology using computational and quantitative methods. In and out of the classroom, students learn to apply the tools of statistics, mathematics, computer science and informatics to biological problems. Vibrant and innovative research in these fields provides exciting interactions between biological and computational scientists. Because CBB is based in the Duke Center for Genomic and Computational Biology (GCB), it offers a unique opportunity for students to become tomorrow's leaders in genome sciences.

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Meet A Faculty Member

  • Professor of Biology

    One of the greatest unsolved questions in biology is how continuous processes of evolutionary change produce the discontinuous groups known as species. For a many years, my team studied hybrid sterility and behavioral mate preferences using classical, QTL-based, or molecular genetic approaches on Drosophila species as model organisms. More recently, the availability of multiple whole-genome sequences (some public but especially those we have obtained ourselves) has dramatically enhanced the scope of progress we make.  A major question we've sought to address has been determining the genetic features and evolutionary processes that allow hybridizing species to persist, with particular interest in recombination and chromosomal inversions. In addition to questions in speciation, we are broadly interested in molecular evolution within species, again with a particular focus on the effects of recombination. See my lab web page for more information.

    Research in my laboratory strives to understand what genetic changes contribute to the formation of new species, and how the process of genetic recombination affects both species formation and molecular evolution. I've been fascinated at how often genetic recombination plays a major role in any evolutionary genetic question I seek to pursue, so understanding its causes and effects has become a thread uniting the dissertations of most people in the laboratory. Our approaches combine classical genetic, molecular genetic, and genomic/ bioinformatic analyses, along with occasional forays into areas like animal behavior (in relation to speciation). I am also very interested in helping develop educational activities (K-12 or college) in genetics and evolution. See my lab webpage for more detailed information: <a href="">

Peter Tonner

5th year CBB Student Amy Schmid Lab
Oct 25
Florian Wagner, CBB PhD Student from the Dave Lab
The Edge (Bostock library, first floor)

Module 1: Becoming a Python power user

Oct 26
Peter Tonner, CBB PhD Student from the Schmid Lab
CBB Student Seminar

Bayesian Hierarchical Model of Microbial Population Growth

Oct 27
Florian Wagner, CBB PhD Student from the Dave Lab
The Edge (Bostock library, first floor)

Module 2: Machine learning in Python