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@ARTICLE{Fadini:641758,
      author       = {Fadini, Alisia and Apostolopoulou, Virginia and Lane,
                      Thomas and van Thor, Jasper},
      title        = {{D}enoising and iterative phase recovery reveal
                      low-occupancy populations in protein crystals},
      journal      = {Communications biology},
      volume       = {8},
      number       = {1},
      issn         = {2399-3642},
      address      = {London},
      publisher    = {Springer Nature},
      reportid     = {PUBDB-2025-05169},
      pages        = {1649},
      year         = {2025},
      abstract     = {Advances in structural biology increasingly focus on
                      uncovering protein dynamics and transient macromolecular
                      complexes. Such studies require modeling of low-occupancy
                      species like time-evolving intermediates and bound ligands.
                      In protein crystallography, difference maps that compare
                      paired perturbed and reference datasets are a powerful way
                      to identify and aid modeling of low-occupancy species.
                      Current methods to generate difference maps, however, rely
                      on manually tuned parameters and, when signals are weak due
                      to low occupancy, can fail to extract clear, chemically
                      interpretable signals. We address these issues, first by
                      showing that negentropy – a measure of how different a
                      signal looks from anticipated Gaussian noise – is an
                      effective metric to assess difference map quality and can
                      therefore be used to automatically determine difference map
                      calculation parameters. Leveraging this, we apply total
                      variation denoising, an image restoration technique that
                      requires a choice of regularization parameter, to
                      crystallographic difference maps. We show that total
                      variation denoising improves map signal-to-noise and enables
                      us to estimate the latent phase contribution of
                      low-occupancy states. We implement this technology in an
                      open-source Python package, METEOR. METEOR opens new
                      possibilities, for time-resolved and ligand-screening
                      crystallography especially, allowing detection of
                      low-occupancy states that could not previously be resolved.},
      cin          = {FS-CFEL-1-PBIO},
      ddc          = {570},
      cid          = {I:(DE-H253)FS-CFEL-1-PBIO-20210408},
      pnm          = {633 - Life Sciences – Building Blocks of Life: Structure
                      and Function (POF4-633) / Helmholtz Young Investigators
                      Group: Structure of Matter (HGF-YIG-Matter) / AIM, DFG
                      project G:(GEPRIS)390715994 - EXC 2056: CUI: Advanced
                      Imaging of Matter (390715994)},
      pid          = {G:(DE-HGF)POF4-633 / G:(DE-HGF)HGF-YIG-Matter /
                      G:(GEPRIS)390715994},
      experiment   = {EXP:(DE-MLZ)NOSPEC-20140101},
      typ          = {PUB:(DE-HGF)16},
      doi          = {10.1038/s42003-025-09031-6},
      url          = {https://bib-pubdb1.desy.de/record/641758},
}