sRNAbench: profiling of small RNAs and its sequence variants in single or multi-species high-throughput experiments

Author(s):  
Guillermo Barturen ◽  
Antonio Rueda ◽  
Maarten Hamberg ◽  
Angel Alganza ◽  
Ricardo Lebron ◽  
...  
2009 ◽  
Vol 10 (1) ◽  
Author(s):  
Clark D Jeffries ◽  
William O Ward ◽  
Diana O Perkins ◽  
Fred A Wright

Genomics Data ◽  
2015 ◽  
Vol 3 ◽  
pp. 1-3 ◽  
Author(s):  
Muhammad Awais Ghani ◽  
Junxing Li ◽  
Linli Rao ◽  
Muhammad Ammar Raza ◽  
Liwen Cao ◽  
...  

2005 ◽  
Vol 13 (03) ◽  
pp. 287-298 ◽  
Author(s):  
JUN CAI ◽  
YING HUANG ◽  
LIANG JI ◽  
YANDA LI

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.


Author(s):  
Samuel D. Stimple ◽  
Ashwin Lahiry ◽  
Joseph E. Taris ◽  
David W. Wood ◽  
Richard A. Lease

2021 ◽  
Vol 871 ◽  
pp. 20-26
Author(s):  
Yu Gao ◽  
Hong Yu ◽  
Yu Zhou ◽  
Xin Jie Zhu ◽  
Qun Bo Fan

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.


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

2020 ◽  
Vol 17 (12) ◽  
pp. 1207-1213
Author(s):  
Yi Zhao ◽  
Matthew G. Sampson ◽  
Xiaoquan Wen

Sign in / Sign up

Export Citation Format

Share Document