scholarly journals Whole-Genome Annotation with BRAKER

Author(s):  
Katharina J. Hoff ◽  
Alexandre Lomsadze ◽  
Mark Borodovsky ◽  
Mario Stanke
Genomics ◽  
2020 ◽  
Author(s):  
Xinshuai Zhang ◽  
Yao Ruan ◽  
Wukang Liu ◽  
Qian Chen ◽  
Lihong Gu ◽  
...  

2020 ◽  
Author(s):  
Rachel C.W. Chan ◽  
Matthew McNeil ◽  
Eric G. Roberts ◽  
Mickaël Mendez ◽  
Maxwell W. Libbrecht ◽  
...  

AbstractSegmentation and genome annotation methods automatically discover joint signal patterns in whole genome datasets. Previously, researchers trained these algorithms in a fully unsupervised way, with no prior knowledge of the functions of particular regions. Adding information provided by expert-created annotations to supervise training could improve the annotations created by these methods. We implemented semi-supervised learning using virtual evidence in the annotation method Segway. Additionally, we defined a positionally tolerant precision and recall metric for scoring genome annotations based on the proximity of each annotation feature to the truth set. We demonstrate semi-supervised Segway’s ability to learn patterns corresponding to provided transcription start sites on a specified supervision label, and subsequently recover other transcription start sites in unseen data on the same supervision label.


2019 ◽  
Vol 99 (4) ◽  
pp. 589-609 ◽  
Author(s):  
Vikash Kumar ◽  
Matthieu Hainaut ◽  
Nicolas Delhomme ◽  
Chanaka Mannapperuma ◽  
Peter Immerzeel ◽  
...  

Genomics Data ◽  
2016 ◽  
Vol 8 ◽  
pp. 45-46 ◽  
Author(s):  
Joon-Hee Han ◽  
Jae-Kyung Chon ◽  
Jong-Hwa Ahn ◽  
Ik-Young Choi ◽  
Yong-Hwan Lee ◽  
...  

2004 ◽  
Vol 101 (9) ◽  
pp. 2888-2893 ◽  
Author(s):  
U. Karaoz ◽  
T. M. Murali ◽  
S. Letovsky ◽  
Y. Zheng ◽  
C. Ding ◽  
...  

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