Is PXRD the gold standard in high throughput experiments?

In post-genomic biology, researchers in the field of proteome focus their attention on the networks of protein interactions that control the lives of cells and organisms. Protein-protein interactions play a useful role in dynamic cellular machinery. In this paper, we developed a method to infer protein-protein interactions based on the theory of support vector machine (SVM). For a given pair of proteins, a new strategy of calculating cross-correlation function of mRNA expression profiles was used to encode SVM vectors. We compared the performance with other methods of inferring protein-protein interaction. Results suggested that, through five-fold cross validation, our SVM model achieved a good prediction. It enables us to show that expression profiles in transcription level can be used to distinguish physical or functional interactions of proteins as well as sequence contents. Lastly, we applied our SVM classifier to evaluate data quality of interaction data sets from four high-throughput experiments. The results show that high-throughput experiments sacrifice some accuracy in determination of interactions because of limitation of experiment technologies.

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Constrained non-negative matrix factorization enabling real-time insights of in situ and high-throughput experiments

Applied Physics Reviews ◽

10.1063/5.0052859 ◽

2021 ◽

Vol 8 (4) ◽

pp. 041410

Author(s):

Phillip M. Maffettone ◽

Aidan C. Daly ◽

Daniel Olds

Keyword(s):

Real Time ◽

High Throughput ◽

Matrix Factorization ◽

High Throughput Experiments ◽

Non Negative Matrix Factorization

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High-Throughput Characterization of Composition and Performance of Titanium Alloys Based on Nanoindentation Technology and EPMA

Key Engineering Materials ◽

10.4028/www.scientific.net/kem.871.20 ◽

2021 ◽

Vol 871 ◽

pp. 20-26

Author(s):

Yu Gao ◽

Hong Yu ◽

Yu Zhou ◽

Xin Jie Zhu ◽

Qun Bo Fan

Keyword(s):

Titanium Alloy ◽

High Throughput ◽

Alloy Composition ◽

Analysis Method ◽

Experimental Scheme ◽

Test Efficiency ◽

And Performance ◽

High Throughput Experiments ◽

The Relationship

Traditional high-throughput experiments increase the test efficiency by designing component gradient tests and other methods. This article intends to improve the traditional high-throughput experiments and proposes an experimental scheme combining nanoindentation technology and electron probe microanalysis (EPMA). Based on a new Ti-Mo-Al-Zr-Cr-Sn alloy, micro-region composition and corresponding performance at multiple indentations are directly characterized, including a series of different alloy compositions composed of 8 elements such as Mo, Al and the corresponding hardness (H) and elastic modulus (E). Then the principal analysis method in statistics, the theory of molybdenum equivalent and aluminum equivalent are used to process the obtained data, and a series of atlases such as "E-H-component characteristic parameters" and "E-H-alloy equivalents" are constructed, which has achieved high-throughput characterization of the relationship between composition and performance of titanium alloy. Related work can not only quickly determine the alloy composition range corresponding to high E and high H values, but also provide guidance for further optimization of titanium alloy composition design.

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