scholarly journals Ancestors graph and an upper bound for the subword complexity function

2013 ◽  
Vol 468 ◽  
pp. 69-82
Author(s):  
Delalleau Guillaume
Keyword(s):  
Upper Bound ◽  
Complexity Function ◽  
Subword Complexity

scholarly journals Improved Prediction of Regulatory Element Using Hybrid Abelian Complexity Features with DNA Sequences

2019 ◽  
Vol 20 (7) ◽  
pp. 1704 ◽  
Author(s):  
Chengchao Wu ◽  
Jin Chen ◽  
Yunxia Liu ◽  
Xuehai Hu
Keyword(s):  
Dna Sequences ◽  
Regulatory Element ◽  
Superior Performance ◽  
Accurate Identification ◽  
Complexity Function ◽  
Enhancer Prediction ◽  
Complex Extension ◽  
Subword Complexity ◽  
Core Issues ◽  
Broad Interest

Abstract: Deciphering the code of cis-regulatory element (CRE) is one of the core issues of current biology. As an important category of CRE, enhancers play crucial roles in gene transcriptional regulations in a distant manner. Further, the disruption of an enhancer can cause abnormal transcription and, thus, trigger human diseases, which means that its accurate identification is currently of broad interest. Here, we introduce an innovative concept, i.e., abelian complexity function (ACF), which is a more complex extension of the classic subword complexity function, for a new coding of DNA sequences. After feature selection by an upper bound estimation and integration with DNA composition features, we developed an enhancer prediction model with hybrid abelian complexity features (HACF). Compared with existing methods, HACF shows consistently superior performance on three sources of enhancer datasets. We tested the generalization ability of HACF by scanning human chromosome 22 to validate previously reported super-enhancers. Meanwhile, we identified novel candidate enhancers which have supports from enhancer-related ENCODE ChIP-seq signals. In summary, HACF improves current enhancer prediction and may be beneficial for further prioritization of functional noncoding variants.

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