dna machine
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Talanta ◽  
2021 ◽  
pp. 123037
Author(s):  
Lan Lin ◽  
Yingying Zhang ◽  
Qiongying Wei ◽  
Hongguang Lin ◽  
Xiaoping Li ◽  
...  

2021 ◽  
pp. 131041
Author(s):  
Na Wu ◽  
Hui-Chao Zhang ◽  
Xu-Hong Sun ◽  
Feng-Na Guo ◽  
Li-Xia Feng ◽  
...  

Author(s):  
Yeqing Wan ◽  
Gaiping Li ◽  
Lina Zou ◽  
Hong Wang ◽  
Qing Wang ◽  
...  

2021 ◽  
Vol 339 ◽  
pp. 129877
Author(s):  
Jialong Wang ◽  
Shunjun Xie ◽  
Dengren Liu ◽  
Hong Zhou ◽  
Li Wang ◽  
...  

2021 ◽  
Author(s):  
chaohui chen ◽  
Rongxiang He ◽  
Xiaoyun Liu ◽  
Zhengtao Zhang ◽  
Long Chen

MicroRNAs play important roles in disease diagnosis and therapy. However, current methods for microRNAs detection suffer from low sensitivity and can’t directly detect short microRNAs. Herein, we have developed a...


eLife ◽  
2020 ◽  
Vol 9 ◽  
Author(s):  
David E Cook ◽  
H Martin Kramer ◽  
David E Torres ◽  
Michael F Seidl ◽  
Bart P H J Thomma

Genomes store information at scales beyond the linear nucleotide sequence, which impacts genome function at the level of an individual, while influences on populations and long-term genome function remains unclear. Here, we addressed how physical and chemical DNA characteristics influence genome evolution in the plant pathogenic fungus Verticillium dahliae. We identified incomplete DNA methylation of repetitive elements, associated with specific genomic compartments originally defined as Lineage-Specific (LS) regions that contain genes involved in host adaptation. Further chromatin characterization revealed associations with features such as H3 Lys-27 methylated histones (H3K27me3) and accessible DNA. Machine learning trained on chromatin data identified twice as much LS DNA as previously recognized, which was validated through orthogonal analysis, and we propose to refer to this DNA as adaptive genomic regions. Our results provide evidence that specific chromatin profiles define adaptive genomic regions, and highlight how different epigenetic factors contribute to the organization of these regions.


2020 ◽  
Vol 92 (14) ◽  
pp. 9764-9771 ◽  
Author(s):  
Shuang Liu ◽  
Xiaoxiao Yu ◽  
Jialong Wang ◽  
Dengren Liu ◽  
Li Wang ◽  
...  

2020 ◽  
Vol 48 (10) ◽  
pp. e60-e60 ◽  
Author(s):  
Jie Wei ◽  
Huimin Wang ◽  
Xue Gong ◽  
Qing Wang ◽  
Hong Wang ◽  
...  

Abstract The construction of robust, modular and compact DNA machinery facilitates us to build more intelligent and ingenious sensing strategies in complex biological systems. However, the performance of conventional DNA amplifiers is always impeded by their limited in-depth amplifications and miscellaneously enzymatic requirements. Here, a proteinase-free reciprocal DNA replication machinery is developed by exploiting the synergistic cross-activation between hybridization chain reaction (HCR) and DNAzyme. The DNAzyme provides an efficient way to simplify the sophisticated design of HCR machinery and simultaneously to promote the amplification capacity. And the HCR-assembled tandem DNAzyme nanowires produce numerous new triggers for reversely stimulating HCR amplifier as systematically explored by experiments and computer-aided simulations. The reciprocal amplifier can be executed as a versatile and powerful sensing platform for analyzing miRNA in living cells and even in mice, originating from the inherent reaction accelerations and multiple-guaranteed recognitions. The reciprocal catalytic DNA machine holds great potential in clinical diagnosis and assessment.


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