scholarly journals A DDX6-CNOT1 Complex and W-Binding Pockets in CNOT9 Reveal Direct Links between miRNA Target Recognition and Silencing

2014 ◽  
Vol 54 (5) ◽  
pp. 737-750 ◽  
Author(s):  
Ying Chen ◽  
Andreas Boland ◽  
Duygu Kuzuoğlu-Öztürk ◽  
Praveen Bawankar ◽  
Belinda Loh ◽  
...  
Keyword(s):  
Mirna Target ◽  
Target Recognition ◽  
Binding Pockets

scholarly journals Beyond the seed: structural basis for supplementary microRNA targeting

2018 ◽  
Author(s):  
Jessica Sheu-Gruttadauria ◽  
Yao Xiao ◽  
Luca F. R. Gebert ◽  
Ian J. MacRae
Keyword(s):  
Mirna Target ◽  
Target Recognition ◽  
Structural Basis ◽  
Seed Region ◽  
Base Pairs ◽  
Argonaute Proteins ◽  
Target Rna ◽  
Mirna Seed ◽  
Mirna Targeting

AbstractmicroRNAs (miRNA) guide Argonaute proteins to mRNAs targeted for repression. Target recognition occurs primarily through the miRNA seed region, composed of guide (g) nucleotides g2–g8. However, nucleotides beyond the seed are also important for some known miRNA-target interactions. Here, we report the structure of human Argonaute2 (Ago2) engaged with a target RNA recognized through both miRNA seed and supplementary (g13–g16) regions. Ago2 creates a “supplementary chamber” that accommodates up to 5 miRNA-target base pairs. Seed and supplementary chambers are adjacent to each other, and can be bridged by an unstructured target loop of 1–15 nucleotides. Opening of the supplementary chamber may be constrained by tension in the miRNA 3' tail as increases in miRNA length stabilize supplementary interactions. Contrary to previous reports, we demonstrate optimal supplementary interactions can increase target affinity >20-fold. These results provide a mechanism for extended miRNA-targeting, suggest a function for 3' isomiRs in tuning miRNA targeting specificity, and indicate that supplementary interactions may contribute more to target recognition than is widely appreciated.

Long range target recognition and identification of camouflaged armored vehicles.

1979 ◽  
Author(s):  
William L. Warnick ◽  
Garvin D. Chastain ◽  
William H. Ton
Keyword(s):  
Long Range ◽  
Target Recognition ◽  
Armored Vehicles

Target recognition on complex displays.

1959 ◽  
Author(s):  
Charles A. Baker ◽  
Dominic F. Morris ◽  
William C. Steedman
Keyword(s):  
Target Recognition

SVM-based global vision system of sports competition and action recognition

2020 ◽  
pp. 1-12
Author(s):  
Changxin Sun ◽  
Di Ma
Keyword(s):  
Target Recognition ◽  
Vision System ◽  
Task Assignment ◽  
Recognition Algorithm ◽  
Control Factor ◽  
Training Time ◽  
Adaboost Algorithm ◽  
Advantages And Disadvantages ◽  
Time Control ◽  
Correlation Degree

In the research of intelligent sports vision systems, the stability and accuracy of vision system target recognition, the reasonable effectiveness of task assignment, and the advantages and disadvantages of path planning are the key factors for the vision system to successfully perform tasks. Aiming at the problem of target recognition errors caused by uneven brightness and mutations in sports competition, a dynamic template mechanism is proposed. In the target recognition algorithm, the correlation degree of data feature changes is fully considered, and the time control factor is introduced when using SVM for classification,At the same time, this study uses an unsupervised clustering method to design a classification strategy to achieve rapid target discrimination when the environmental brightness changes, which improves the accuracy of recognition. In addition, the Adaboost algorithm is selected as the machine learning method, and the algorithm is optimized from the aspects of fast feature selection and double threshold decision, which effectively improves the training time of the classifier. Finally, for complex human poses and partially occluded human targets, this paper proposes to express the entire human body through multiple parts. The experimental results show that this method can be used to detect sports players with multiple poses and partial occlusions in complex backgrounds and provides an effective technical means for detecting sports competition action characteristics in complex backgrounds.

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