Project abstract X-ray crystallography and cryoEM single particle reconstruction (cryoEM SPR) generate uniquely detailed structural information that is used to: (1) understand cellular processes at the molecular level, (2) explain and validate results obtain by other biochemical, biophysical and cell biology methods, and also (3) guide drug design studies. All these applications are highly relevant to the NIH mission. The proposal aims to advance data analysis methods for X-ray and cryoEM diffraction and cryoEM SPR so that reliable and informative structural models can be obtained from micro- and nanocrystals with both techniques as well as from single molecules (particles) with electron microscopy. The PI aims to expand X-ray crystallography and cryoEM SPR methods to new areas by highly hierarchical application of data mining and dimensionality reduction methods. The data richness generated by recent changes in hardware enables deep exploration of much more elaborate, non-random start algorithms that have better convergence than the random start methods that are frequently used in computational approaches. In diffraction methods, one frequently needs to combine data from multiple crystals for successful structure solution. However, optimal averaging should only consider data that represent the same structural source of diffraction patterns, so there is a fundamental need to segregate individual samples into distinct groups that are internally isomorphous. In traditional approaches, complex non-isomorphism patterns result in combinatorial complexity of data analysis in the presence of incompleteness and low signal-to-noise for individually contributing datasets. The PI will develop methods addressing this long-standing unsolved problem, with the methods having potential to also advance the analysis of biologically relevant structural variability that manifests as non- isomorphism in experimental date. In cryoEM diffraction, data analysis does not yet produce reliable structural results consistently, de novo structure solution is limited to a small number of projects where direct methods can be used, and for small molecules, determination of absolute configuration remains a challenge. The PI will develop and implement experimental and computational solutions to advance modeling of systematic effects encountered in electron diffraction and to expand phasing approaches in electron crystallography to address these outstanding problems. The PI will also work on developing estimators of bias magnitude and debiasing procedures to expand cryoEM SPR so that much smaller particles can be modelled reliably. Finally, the PI will develop approaches relying on comparative genomics so that structural models can be built and validated at very low resolution that are currently outside of the reach for molecular interpretation. All research will rely on the strong expertise of the PI in selected areas.