TargetDBP: Accurate DNA-Binding Protein Prediction via Sequence-based Multi-View Feature Learning

What is it about?

Accurately identifying DNA-binding proteins (DBPs) from protein sequence information is an important but challenging task for protein function annotations. Here, We establish a novel computational method, named TargetDBP, for accurately targeting DBPs from primary sequences. The TargetDBP web server and datasets are freely available at http://csbio.njust.edu.cn/bioinf/targetdbp/ for academic use.

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Why is it important?

Interactions between proteins and DNA are indispensable for biological activities and play vital roles in a wide variety of biological processes, such as gene regulation, DNA replication and repair [1]. Hence, accurately targeting DNA-binding proteins (DBPs) is of significant importance for the annotation of protein functions. Accurately identifying DNA-binding proteins (DBPs) from protein sequence information is an important but challenging task for protein function annotations. Identification of DBPs via wet-lab experimental technologies is often cost-intensive and time-consuming. Facing the difficulty in experimentally identifying DBPs and the avalanche of new protein sequences generated in the post-genomic age [2], it is highly desired to develop an automatic computational method for rapidly and accurately targeting DBPs.

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