scholarly journals Coupling High-Throughput Experiments and Regression Algorithms to Optimize PGM-Free ORR Electrocatalyst Synthesis

2020 ◽  
Vol 3 (9) ◽  
pp. 9083-9088 ◽  
Author(s):  
Mohammad Rezaul Karim ◽  
Magali Ferrandon ◽  
Samantha Medina ◽  
Elliot Sture ◽  
Nancy Kariuki ◽  
...  
Keyword(s):  
High Throughput ◽  
Regression Algorithms ◽  
High Throughput Experiments

scholarly journals Discovering collectively informative descriptors from high-throughput experiments

2009 ◽  
Vol 10 (1) ◽  
Author(s):  
Clark D Jeffries ◽  
William O Ward ◽  
Diana O Perkins ◽  
Fred A Wright
Keyword(s):  
High Throughput ◽  
High Throughput Experiments

INFERRING PROTEIN-PROTEIN INTERACTIONS FROM MESSENGER RNA EXPRESSION PROFILES WITH SVM

2005 ◽  
Vol 13 (03) ◽  
pp. 287-298 ◽  
Author(s):  
JUN CAI ◽  
YING HUANG ◽  
LIANG JI ◽  
YANDA LI
Keyword(s):  
High Throughput ◽  
Protein Interactions ◽  
Messenger Rna ◽  
Expression Profiles ◽  
Support Vector ◽  
Svm Classifier ◽  
Good Prediction ◽  
Protein Protein Interactions ◽  
Protein Protein Interaction ◽  
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.

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

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.

scholarly journals Quantify and control reproducibility in high-throughput experiments

2020 ◽  
Vol 17 (12) ◽  
pp. 1207-1213
Author(s):  
Yi Zhao ◽  
Matthew G. Sampson ◽  
Xiaoquan Wen
Keyword(s):  
High Throughput ◽  
High Throughput Experiments ◽  
And Control

scholarly journals Quantitative reproducibility analysis for identifying reproducible targets from high-throughput experiments

2017 ◽  
Vol 11 (1) ◽  
Author(s):  
Wenfei Zhang ◽  
Ying Liu ◽  
Mindy Zhang ◽  
Cheng Zhu ◽  
Yuefeng Lu
Keyword(s):  
High Throughput ◽  
High Throughput Experiments

scholarly journals The sva package for removing batch effects and other unwanted variation in high-throughput experiments

2012 ◽  
Vol 28 (6) ◽  
pp. 882-883 ◽  
Author(s):  
Jeffrey T. Leek ◽  
W. Evan Johnson ◽  
Hilary S. Parker ◽  
Andrew E. Jaffe ◽  
John D. Storey
Keyword(s):  
High Throughput ◽  
Batch Effects ◽  
High Throughput Experiments

Back Cover: Core-Shell Nanocatalyst Design by Combining High-Throughput Experiments and First-Principles Simulations (ChemCatChem 12/2013)

ChemCatChem ◽  
2013 ◽  
Vol 5 (12) ◽  
pp. 3914-3914
Author(s):  
Nageswara Rao Peela ◽  
Weiqing Zheng ◽  
Ivan C. Lee ◽  
Ayman M. Karim ◽  
Dionisios G. Vlachos
Keyword(s):  
High Throughput ◽  
First Principles ◽  
Core Shell ◽  
Back Cover ◽  
High Throughput Experiments
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