Discriminating between HuR and TTP binding sites using the k-spectrum kernel method.

ABSTRACT:

Background

The RNA binding proteins (RBPs) human antigen R (HuR) and Tristetraprolin (TTP) are known to exhibit competitive binding but have opposing effects on the bound messenger RNA (mRNA). How cells discriminate between the two proteins is an interesting problem. Machine learning approaches, such as support vector machines (SVMs), may be useful in the identification of discriminative features. However, this method has yet to be applied to studies of RNA binding protein motifs.

Results

Applying the k-spectrum kernel to a support vector machine (SVM), we first verified the published binding sites of both HuR and TTP. Additional feature engineering highlighted the U-rich binding preference of HuR and AU-rich binding preference for TTP. Domain adaptation along with multi-tas

SUBMITTER: Bhandare S 

PROVIDER: S-EPMC5363848 | biostudies-literature | 2017

REPOSITORIES: biostudies-literature