# Distance Geometry and Geometric Algebra for Protein Structure Determination

Protein structure determination using data from Nuclear Magnetic Resonance (NMR) experiments is one of the most important problems in Distance Geometry. Protein geometry allow us to define an atomic ordering such that a combinatorial approach can be applied to solve the problem. In order to consider the uncertainties in NMR data, we will discuss a new model to represent protein structures using the 5D Conformal Space and a language more powerful than Linear Algebra: Geometric Algebra.

*Carlile Lavor graduated in Mathematics from the University of Campinas, in 1996, and received a Ph.D. in Computer Science from the Federal University of Rio de Janeiro, in 2001. He was Visiting Professor in distinguished institutions like École Polytechnique (2008-2009) and Duke University (2013-2014). Since 2015, he is a full professor at the University of Campinas. His research efforts to Distance Geometry, in the last 15 years, culminated with the publication of a paper (co-authored by Liberti, Maculan, and Mucherino) in SIAM Review (first issue in 2014), which was awarded the Notable Article Prize from the ACM Computing Reviews in 2015. He is co-author of the books "Euclidean Distance Geometry" and "A Geometric Algebra Invitation to Space-Time Physics, Robotics and Molecular Geometry", both by Springer. Carlile Lavor is the current President of the Brazilian Society of Applied and Computational Mathematics.*