Rational Screening Set Design and Compound Selection:  Cascaded Clustering

1998 ◽  
Vol 38 (3) ◽  
pp. 497-505 ◽  
Author(s):  
Paul R. Menard ◽  
Richard A. Lewis ◽  
Jonathan S. Mason
2006 ◽  
Vol 27 (2) ◽  
pp. 260-288
Author(s):  
Tanit Mendes ◽  
Janet Tulloch
Keyword(s):  

Plant Methods ◽  
2021 ◽  
Vol 17 (1) ◽  
Author(s):  
Peio Ziarsolo ◽  
Tomas Hasing ◽  
Rebeca Hilario ◽  
Victor Garcia-Carpintero ◽  
Jose Blanca ◽  
...  

Abstract Background K-seq, a new genotyping methodology based on the amplification of genomic regions using two steps of Klenow amplification with short oligonucleotides, followed by standard PCR and Illumina sequencing, is presented. The protocol was accompanied by software developed to aid with primer set design. Results As the first examples, K-seq in species as diverse as tomato, dog and wheat was developed. K-seq provided genetic distances similar to those based on WGS in dogs. Experiments comparing K-seq and GBS in tomato showed similar genetic results, although K-seq had the advantage of finding more SNPs for the same number of Illumina reads. The technology reproducibility was tested with two independent runs of the tomato samples, and the correlation coefficient of the SNP coverages between samples was 0.8 and the genotype match was above 94%. K-seq also proved to be useful in polyploid species. The wheat samples generated specific markers for all subgenomes, and the SNPs generated from the diploid ancestors were located in the expected subgenome with accuracies greater than 80%. Conclusion K-seq is an open, patent-unencumbered, easy-to-set-up, cost-effective and reliable technology ready to be used by any molecular biology laboratory without special equipment in many genetic studies.


2005 ◽  
Vol 13 (2) ◽  
pp. 135-143 ◽  
Author(s):  
Pascal Dufour ◽  
Sharad Bhartiya ◽  
Prasad S. Dhurjati ◽  
Francis J. Doyle III

STORIA URBANA ◽  
2009 ◽  
pp. 47-67
Author(s):  
Claudia Lamberti

- The essay compares the images of the city defined by the Expressionist movement and the city images in the films of the time. Expressionist architects discovered that film-set design gave them a chance to experiment with their artistic skills. At the same time, film studios could not shoot outdoors easily and so were forced to rely on constructed sets. All this worked out as an incentive for architectural invention. Sets became an apt proving ground for the new expressiveness of the architects as well as a way to experiment with the use of space without limits and constraints. This essay examines the cases of 6 films whose elements are specifically and directly attributable to the Expressionist culture. Here the case of the city encompasses both set design and the urban atmosphere in films linked with the avant-garde movements. The essay also provides a filmography of the most important films with urban settings shot by German artists in the 1920s and 1930s.


Friends ◽  
2019 ◽  
pp. 125-167
Author(s):  
Simone Knox ◽  
Kai Hanno Schwind
Keyword(s):  

1986 ◽  
Vol 3 (2) ◽  
pp. 151-172 ◽  
Author(s):  
Jerome F. Parmer ◽  
Robert W. Baldi ◽  
Ken L. Agarwal ◽  
Richard A. Sutton ◽  
Mark W. Liggett

BMJ Open ◽  
2021 ◽  
Vol 11 (12) ◽  
pp. e050146
Author(s):  
Jenna M Reps ◽  
Patrick Ryan ◽  
P R Rijnbeek

ObjectiveThe internal validation of prediction models aims to quantify the generalisability of a model. We aim to determine the impact, if any, that the choice of development and internal validation design has on the internal performance bias and model generalisability in big data (n~500 000).DesignRetrospective cohort.SettingPrimary and secondary care; three US claims databases.Participants1 200 769 patients pharmaceutically treated for their first occurrence of depression.MethodsWe investigated the impact of the development/validation design across 21 real-world prediction questions. Model discrimination and calibration were assessed. We trained LASSO logistic regression models using US claims data and internally validated the models using eight different designs: ‘no test/validation set’, ‘test/validation set’ and cross validation with 3-fold, 5-fold or 10-fold with and without a test set. We then externally validated each model in two new US claims databases. We estimated the internal validation bias per design by empirically comparing the differences between the estimated internal performance and external performance.ResultsThe differences between the models’ internal estimated performances and external performances were largest for the ‘no test/validation set’ design. This indicates even with large data the ‘no test/validation set’ design causes models to overfit. The seven alternative designs included some validation process to select the hyperparameters and a fair testing process to estimate internal performance. These designs had similar internal performance estimates and performed similarly when externally validated in the two external databases.ConclusionsEven with big data, it is important to use some validation process to select the optimal hyperparameters and fairly assess internal validation using a test set or cross-validation.


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