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.
Computational & discrete geometry: Paradigms & techniques, approximation algorithms, geometric optimization, kinetic geometry, data structures, arrangements, proximity problems, trangulation, motion planning, geometric sampling.
Shape Analysis: Representation, matching, clustering, similarity searching.
GIS and ecologic modeling: Terrain modeling and analysis, navigation, visibility, flow analysis, ecological modeling.
Spatial databases: Indexing techniques, spatiotemporal databases, stream processing, continuous queries, network data management.
Sensor networks: Processing sensor data, communication and energy efficient algorithms, sensor network design, sensor networks for ecological modeling.
Trajectory data analysis: Trajectory segmentation, matching, clustering, answering queries.
Computational and combinatorial geometry, computational biology, robotics, spatial databases, geographic molecular information systems, and data structures.