期刊
JOURNAL OF GLOBAL OPTIMIZATION
卷 83, 期 1, 页码 3-28出版社
SPRINGER
DOI: 10.1007/s10898-021-01004-3
关键词
NMR spectroscopy; Shortest path problem; Resonance assignment problem; Linear programming relaxation
资金
- NSF BIGDATAaward [IIS-1837992]
- NIH/NIGMS award [1R01GM136780-01]
- AFOSR [FA9550-17-1-0291]
- Simons Foundation Math+X Investigator Award
- Moore Foundation Data-Driven Discovery Investigator Award
- NIH [GM-117212]
Nuclear Magnetic Resonance (NMR) Spectroscopy is a key technique for protein structure determination, with a challenge being the assignment of resonance frequencies to atoms. The introduction of LIAN, a novel linear programming formulation, has led to state-of-the-art results in simulated and experimental datasets.
Nuclear Magnetic Resonance (NMR) Spectroscopy is the second most used technique (after X-ray crystallography) for structural determination of proteins. A computational challenge in this technique involves solving a discrete optimization problem that assigns the resonance frequency to each atom in the protein. This paper introduces LIAN (LInear programming Assignment for NMR), a novel linear programming formulation of the problem which yields state-of-the-art results in simulated and experimental datasets.
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