Special Issue "Multivariate Analysis Applications to Crystallography"
Deadline for manuscript submissions: closed (31 December 2020) | Viewed by 22789
Interests: protein crystallography; phasing methods; modulated enhanced diffraction; multivariate analysis
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The advent of next-generation X-ray sources, more sensitive and fast detectors, and multi-probe experimental setups enable deeper static and dynamic crystallographic investigations. The huge amount of data collected by multi-technique in situ or in operando experiments on powder samples or by serial crystallography experiments on single crystals demand advanced and fast methods of analysis. Multivariate analysis can efficiently process multiple measurements, by considering them as a whole data matrix and in a probe-independent way. This approach is fast, blind, unbiased, and complementary to the traditional approaches to process each measurement independently. It does not require a priori structural information, and can be used as on-site analysis to extract relevant trends in data. Multivariate methods such as principal component analysis and phase-sensitive detection have been used to detect subtle structural changes induced in situ by varying external parameters (temperature, light, etc.). In this context, theoretical frameworks for new techniques like modulated enhanced diffraction have been developed to achieve higher sensitivity and chemical selectivity in X-ray diffraction experiments. On the other hand, established statistical methods such as principal component analysis have been modified (constrained) to address issues related to X-ray diffraction and spectroscopic measurements. New procedures to reduce unwanted peak shifts due to lattice distortion, to automatically extract the structural kinetics, to selectively locate atoms responding to in situ stimulus have been developed and applied. As a new, exciting frontier, artificial intelligence is being applied to high-throughput crystallographic steps such as crystallization screening, indexing, and dataset merging.
This Special Issue will cover computational and experimental advancements related to the use of multivariate analysis in crystallography. Therefore, this Special Issue welcomes original research and review manuscripts on the following aspects of the processing of data collected in crystallographic experiments:
- Data reduction, indexing, integration, and matching between different single-crystal datasets
- Qualitative and quantitative analysis, classification of samples based on diffraction profiles
- Combining data from multi-probe experiments
- Fast extraction of reaction kinetics
- High-sensitivity structural characterization by X-ray powder diffraction and pair distribution function measurements
- Advancements in phasing methods
- Improved interpretation of electron density maps, model validation
Dr. Rocco Caliandro
Prof. Marco Milanesio
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Crystals is an international peer-reviewed open access monthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
- Multivariate methods
- Principal component analysis
- Phase-sensitive detection
- Modulated enhanced diffraction
- On-site analysis