Genome-wide identification and comparative analysis of grafting-responsive mRNA in watermelon grafted onto bottle gourd and squash rootstocks by high-throughput sequencing

2015 ◽  
Vol 291 (2) ◽  
pp. 621-633 ◽  
Author(s):  
Na Liu ◽  
Jinghua Yang ◽  
Xinxing Fu ◽  
Li Zhang ◽  
Kai Tang ◽  
...  
PLoS ONE ◽  
2013 ◽  
Vol 8 (2) ◽  
pp. e57359 ◽  
Author(s):  
Na Liu ◽  
Jinghua Yang ◽  
Shaogui Guo ◽  
Yong Xu ◽  
Mingfang Zhang

2021 ◽  
Vol 167 ◽  
pp. 104077
Author(s):  
Yunhe Ban ◽  
Xiang Li ◽  
Yuqi Li ◽  
Xinyu Li ◽  
Xu Li ◽  
...  

2020 ◽  
Vol 3 (1) ◽  
Author(s):  
Juan Xie ◽  
Jinfang Zheng ◽  
Xu Hong ◽  
Xiaoxue Tong ◽  
Shiyong Liu

AbstractProtein-RNA interaction participates in many biological processes. So, studying protein–RNA interaction can help us to understand the function of protein and RNA. Although the protein–RNA 3D3D model, like PRIME, was useful in building 3D structural complexes, it can’t be used genome-wide, due to lacking RNA 3D structures. To take full advantage of RNA secondary structures revealed from high-throughput sequencing, we present PRIME-3D2D to predict binding sites of protein–RNA interaction. PRIME-3D2D is almost as good as PRIME at modeling protein–RNA complexes. PRIME-3D2D can be used to predict binding sites on PDB data (MCC = 0.75/0.70 for binding sites in protein/RNA) and transcription-wide (MCC = 0.285 for binding sites in RNA). Testing on PDB and yeast transcription-wide data show that PRIME-3D2D performs better than other binding sites predictor. So, PRIME-3D2D can be used to predict the binding sites both on PDB and genome-wide, and it’s freely available.


BMC Genomics ◽  
2020 ◽  
Vol 21 (1) ◽  
Author(s):  
Rongrong Zhai ◽  
Shenghai Ye ◽  
Guofu Zhu ◽  
Yanting Lu ◽  
Jing Ye ◽  
...  

2020 ◽  
Vol 20 (6) ◽  
pp. 825-838
Author(s):  
Xiaoqian Liu ◽  
Shanshan Chu ◽  
Chongyuan Sun ◽  
Huanqing Xu ◽  
Jinyu Zhang ◽  
...  

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