Structural and Functional Bioinformatics Group
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Current Research
Automating Nuclear Magnetic Resonance (NMR) protein structure determination
The SFB group aims to develop automatic tools to accelerate the NMR protein structure determination process, which involves peak picking, resonance assignment, NOE assignment, and structure calculation.
Model, analyze, and control complex biological and biochemical systems
The SFB group aims to model, analyze, and control complex biological systems, such as protein-protein interaction networks, and biochemical systems, such as biochemical reaction networks and gene delivery systems.
Genome-scale domain identification, domain function annotation, domain shuffling
The SFB group aims to study comparative genomics from protein domain level. We are interested in developing efficient algorithms for genome-scale domain identification, domain function annoatation, and detecting tentative novel domains and shuffling domains.
Ab initio protein 3D structure prediction
The SFB group aims to model the high-dimensional protein angle space, model protein loops and side-chains, and design statistical measurement for model assessment.
Machine learning methods for biological problems
The SFB group aims to develop and apply machine learning methods to model biological systems.
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The beginning and end dates for each internship will be agreed upon between the Faculty and the Intern. Visa processing time will be a determining factor in actual start date. Minimum period is three months. Maximum period is six months.
Structural and Functional Bioinformatics Group
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