scholarly journals Choosing your (Friedel) mates wisely: grouping data sets to improve anomalous signal

2019 ◽  
Vol 75 (2) ◽  
pp. 200-210 ◽  
Author(s):  
Nicolas Foos ◽  
Michele Cianci ◽  
Max H. Nanao

Single-wavelength anomalous diffraction (SAD) phasing from multiple crystals can be especially challenging in samples with weak anomalous signals and/or strong non-isomorphism. Here, advantage is taken of the combinatorial diversity possible in such experiments to study the relationship between merging statistics and downstream metrics of phasing signals. It is furthermore shown that a genetic algorithm (GA) can be used to optimize the grouping of data sets to enhance weak anomalous signals based on these merging statistics.

2016 ◽  
Vol 72 (3) ◽  
pp. 421-429 ◽  
Author(s):  
Vincent Olieric ◽  
Tobias Weinert ◽  
Aaron D. Finke ◽  
Carolin Anders ◽  
Dianfan Li ◽  
...  

Recent improvements in data-collection strategies have pushed the limits of native SAD (single-wavelength anomalous diffraction) phasing, a method that uses the weak anomalous signal of light elements naturally present in macromolecules. These involve the merging of multiple data sets from either multiple crystals or from a single crystal collected in multiple orientations at a low X-ray dose. Both approaches yield data of high multiplicity while minimizing radiation damage and systematic error, thus ensuring accurate measurements of the anomalous differences. Here, the combined use of these two strategies is described to solve cases of native SAD phasing that were particular challenges: the integral membrane diacylglycerol kinase (DgkA) with a low Bijvoet ratio of 1% and the large 200 kDa complex of the CRISPR-associated endonuclease (Cas9) bound to guide RNA and target DNA crystallized in the low-symmetry space groupC2. The optimal native SAD data-collection strategy based on systematic measurements performed on the 266 kDa multiprotein/multiligand tubulin complex is discussed.


Author(s):  
Tushar ◽  
Tushar ◽  
Shibendu Shekhar Roy ◽  
Dilip Kumar Pratihar

Clustering is a potential tool of data mining. A clustering method analyzes the pattern of a data set and groups the data into several clusters based on the similarity among themselves. Clusters may be either crisp or fuzzy in nature. The present chapter deals with clustering of some data sets using Fuzzy C-Means (FCM) algorithm and Entropy-based Fuzzy Clustering (EFC) algorithm. In FCM algorithm, the nature and quality of clusters depend on the pre-defined number of clusters, level of cluster fuzziness and a threshold value utilized for obtaining the number of outliers (if any). On the other hand, the quality of clusters obtained by the EFC algorithm is dependent on a constant used to establish the relationship between the distance and similarity of two data points, a threshold value of similarity and another threshold value used for determining the number of outliers. The clusters should ideally be distinct and at the same time compact in nature. Moreover, the number of outliers should be as minimum as possible. Thus, the above problem may be posed as an optimization problem, which will be solved using a Genetic Algorithm (GA). The best set of multi-dimensional clusters will be mapped into 2-D for visualization using a Self-Organizing Map (SOM).


2015 ◽  
Vol 71 (12) ◽  
pp. 2519-2525 ◽  
Author(s):  
Takanori Nakane ◽  
Changyong Song ◽  
Mamoru Suzuki ◽  
Eriko Nango ◽  
Jun Kobayashi ◽  
...  

Serial femtosecond crystallography (SFX) allows structures to be determined with minimal radiation damage. However, phasing native crystals in SFX is not very common. Here, the structure determination of native lysozyme from single-wavelength anomalous diffraction (SAD) by utilizing the anomalous signal of sulfur and chlorine at a wavelength of 1.77 Å is successfully demonstrated. This sulfur SAD method can be applied to a wide range of proteins, which will improve the determination of native crystal structures.


2019 ◽  
Vol 75 (1) ◽  
pp. 32-40 ◽  
Author(s):  
Caixia Hou ◽  
Oleg V. Tsodikov

The experimental phase determination of crystal structures of nucleic acids and nucleic acid–ligand complexes would benefit from a facile method. Even for double-stranded DNA, software-generated models are generally insufficiently accurate to serve as molecular replacement search models, necessitating experimental phasing. Here, it is demonstrated that Zn2+ ions coordinated to the N7 atom of guanine bases generate sufficient anomalous signal for single-wavelength anomalous diffraction (SAD) phasing of DNA crystal structures. Using zinc SAD, three crystal structures of double-stranded DNA oligomers, 5′-AGGGATCCCT-3′, 5′-GGGATCCC-3′ and 5′-GAGGCCTC-3′, were determined. By determining the crystal structure of one of these oligomers, GAGGCCTC, in the presence of Mg2+ instead of Zn2+, it was demonstrated that Zn2+ is not structurally perturbing. These structures allowed the analysis of structural changes in the DNA on the binding of analogues of the natural product mithramycin to two of these oligomers, AGGGATCCCT and GAGGCCTC. Zinc SAD may become a routine approach for determining the crystal structures of nucleic acids and their complexes with small molecules.


2007 ◽  
Vol 40 (3) ◽  
pp. 552-558 ◽  
Author(s):  
R. Sanishvili ◽  
C. Besnard ◽  
F. Camus ◽  
M. Fleurant ◽  
P. Pattison ◽  
...  

In this paper the anisotropy of anomalous scattering at the BrK-absorption edge in brominated nucleotides is investigated, and it is shown that this effect can give rise to a marked directional dependence of the anomalous signal strength in X-ray diffraction data. This implies that choosing the correct orientation for crystals of such molecules can be a crucial determinant of success or failure when using single- and multiple-wavelength anomalous diffraction (SAD or MAD) methods to solve their structure. In particular, polarized absorption spectra on an oriented crystal of a brominated DNA molecule were measured, and were used to determine the orientation that yields a maximum anomalous signal in the diffraction data. Out of several SAD data sets, only those collected at or near that optimal orientation allowed interpretable electron density maps to be obtained. The findings of this study have implications for instrumental choices in experimental stations at synchrotron beamlines, as well as for the development of data collection strategy programs.


2016 ◽  
Vol 72 (3) ◽  
pp. 359-374 ◽  
Author(s):  
Thomas C. Terwilliger ◽  
Gábor Bunkóczi ◽  
Li-Wei Hung ◽  
Peter H. Zwart ◽  
Janet L. Smith ◽  
...  

A key challenge in the SAD phasing method is solving a structure when the anomalous signal-to-noise ratio is low. Here, algorithms and tools for evaluating and optimizing the useful anomalous correlation and the anomalous signal in a SAD experiment are described. A simple theoretical framework [Terwilligeret al.(2016),Acta Cryst.D72, 346–358] is used to develop methods for planning a SAD experiment, scaling SAD data sets and estimating the useful anomalous correlation and anomalous signal in a SAD data set. Thephenix.plan_sad_experimenttool uses a database of solved and unsolved SAD data sets and the expected characteristics of a SAD data set to estimate the probability that the anomalous substructure will be found in the SAD experiment and the expected map quality that would be obtained if the substructure were found. Thephenix.scale_and_mergetool scales unmerged SAD data from one or more crystals using local scaling and optimizes the anomalous signal by identifying the systematic differences among data sets, and thephenix.anomalous_signaltool estimates the useful anomalous correlation and anomalous signal after collecting SAD data and estimates the probability that the data set can be solved and the likely figure of merit of phasing.


2019 ◽  
Author(s):  
Jessie Martin ◽  
Jason S. Tsukahara ◽  
Christopher Draheim ◽  
Zach Shipstead ◽  
Cody Mashburn ◽  
...  

**The uploaded manuscript is still in preparation** In this study, we tested the relationship between visual arrays tasks and working memory capacity and attention control. Specifically, we tested whether task design (selection or non-selection demands) impacted the relationship between visual arrays measures and constructs of working memory capacity and attention control. Using analyses from 4 independent data sets we showed that the degree to which visual arrays measures rely on selection influences the degree to which they reflect domain-general attention control.


1993 ◽  
Vol 163 (4) ◽  
pp. 522-534 ◽  
Author(s):  
W. Adams ◽  
R. E. Kendell ◽  
E. H. Hare ◽  
P. Munk-Jørgensen

The epidemiological evidence that the offspring of women exposed to influenza in pregnancy are at increased risk of schizophrenia is conflicting. In an attempt to clarify the issue we explored the relationship between the monthly incidence of influenza (and measles) in the general population and the distribution of birth dates of three large series of schizophrenic patients - 16 960 Scottish patients born in 1932–60; 22 021 English patients born in 1921–60; and 18 723 Danish patients born in 1911–65. Exposure to the 1957 epidemic of A2 influenza in midpregnancy was associated with an increased incidence of schizophrenia, at least in females, in all three data sets. We also confirmed the previous report of a statistically significant long-term relationship between patients' birth dates and outbreaks of influenza in the English series, with time lags of - 2 and - 3 months (the sixth and seventh months of pregnancy). Despite several other negative studies by ourselves and others we conclude that these relationships are probably both genuine and causal; and that maternal influenza during the middle third of intrauterine development, or something closely associated with it, is implicated in the aetiology of some cases of schizophrenia.


2021 ◽  
Vol 99 (Supplement_1) ◽  
pp. 218-219
Author(s):  
Andres Fernando T Russi ◽  
Mike D Tokach ◽  
Jason C Woodworth ◽  
Joel M DeRouchey ◽  
Robert D Goodband ◽  
...  

Abstract The swine industry has been constantly evolving to select animals with improved performance traits and to minimize variation in body weight (BW) in order to meet packer specifications. Therefore, understanding variation presents an opportunity for producers to find strategies that could help reduce, manage, or deal with variation of pigs in a barn. A systematic review and meta-analysis was conducted by collecting data from multiple studies and available data sets in order to develop prediction equations for coefficient of variation (CV) and standard deviation (SD) as a function of BW. Information regarding BW variation from 16 papers was recorded to provide approximately 204 data points. Together, these data included 117,268 individually weighed pigs with a sample size that ranged from 104 to 4,108 pigs. A random-effects model with study used as a random effect was developed. Observations were weighted using sample size as an estimate for precision on the analysis, where larger data sets accounted for increased accuracy in the model. Regression equations were developed using the nlme package of R to determine the relationship between BW and its variation. Polynomial regression analysis was conducted separately for each variation measurement. When CV was reported in the data set, SD was calculated and vice versa. The resulting prediction equations were: CV (%) = 20.04 – 0.135 × (BW) + 0.00043 × (BW)2, R2=0.79; SD = 0.41 + 0.150 × (BW) - 0.00041 × (BW)2, R2 = 0.95. These equations suggest that there is evidence for a decreasing quadratic relationship between mean CV of a population and BW of pigs whereby the rate of decrease is smaller as mean pig BW increases from birth to market. Conversely, the rate of increase of SD of a population of pigs is smaller as mean pig BW increases from birth to market.


2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Eerika Finell ◽  
Asko Tolvanen ◽  
Juha Pekkanen ◽  
Timo Ståhl ◽  
Pauliina Luopa

Abstract Background Little previous research has analysed the relationship between schools’ indoor air problems and schools’ social climate. In this study, we analysed a) whether observed mould and dampness in a school building relates to students’ perceptions of school climate (i.e. teacher-student relationships and class spirit) and b) whether reported subjective indoor air quality (IAQ) at the school level mediates this relationship. Methods The data analysed was created by merging two nationwide data sets: survey data from students, including information on subjective IAQ (N = 25,101 students), and data from schools, including information on mould and dampness in school buildings (N = 222). The data was analysed using multilevel mediational models. Results After the background variables were adjusted, schools’ observed mould and dampness was not significantly related to neither student-perceived teacher-student relationships nor class spirit. However, our mediational models showed that there were significant indirect effects from schools’ observed mould and dampness to outcome variables via school-level subjective IAQ: a) in schools with mould and dampness, students reported significantly poorer subjective IAQ (standardised β = 0.34, p < 0.001) than in schools without; b) the worse the subjective IAQ at school level, the worse the student-reported teacher-student relationships (β = 0.31, p = 0.001) and class spirit (β = 0.25, p = 0.006). Conclusions Problems in a school’s indoor environment may impair the school’s social climate to the degree that such problems decrease the school’s perceived IAQ.


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