Ma, Jianpeng2014-10-172014-10-172013-122013-12-05December 2Zhang, Chong. "Advanced Computational Methods for Macromolecular Modeling and Structure Determination." (2013) Diss., Rice University. <a href="https://hdl.handle.net/1911/77596">https://hdl.handle.net/1911/77596</a>.https://hdl.handle.net/1911/77596As volume and complexity of macromolecules increase, theories and algorithms that deal with structure determination at low X-ray resolution are of particular importance. With limited diffraction data in hand, experimentalists rely on advanced computational tools to extract and utilize useful information, seeking to determinate a three dimensional model that best fits the experiment data. Success of further studies on the property and function of a specific molecule - the key to practical applications - is therefore heavily dependent on the validity and accuracy of the solved structure. In this thesis I propose Deformable Complex Network (DCN) and introduce Normal Mode Analysis (NMA), which are designed to model the average coordinates of atoms and associated fluctuations, respectively. Their applications on structure determination target two major branches ? the positional refinement and temperature factor refinement. I demonstrate their remarkable performance in structure improvements based on several criteria, such as the free R value, overfitting effect and Ramachandran Statistics, with tests carried out across a broad range of real systems for generality and consistency.application/pdfengCopyright is held by the author, unless otherwise indicated. Permission to reuse, publish, or reproduce the work beyond the bounds of fair use or other exemptions to copyright law must be obtained from the copyright holder.Deformable complex networkX-ray refinementHigh-performance computingStructure determinationMacromolecular modelingAlgorithmsLow resolutionAdvanced Computational Methods for Macromolecular Modeling and Structure DeterminationThesis2014-10-17