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Capsule-LPI: a LncRNA–protein interaction predicting tool based on a capsule network by Li, Ying (author);Sun, Hang (author);Feng, Shiyao (author);Zhang, Qi (author);Han, Siyu (author);Du, Wei (author) is a Biochemistry, Genetics and Molecular Biology article available to read on EtoBox.

What is Capsule-LPI: a LncRNA–protein interaction predicting tool based on a capsule network about?

## Background Long noncoding RNAs (lncRNAs) play important roles in multiple biological processes. Identifying LncRNA–protein interactions (LPIs) is key to understanding lncRNA functions. Although some LPIs computational methods have been developed, the LPIs prediction problem remains challenging. How to integrate multimodal features from more perspectives and build deep learning architectures with better recognition performance have always been the focus of research on LPIs. ## Results We present a novel multichannel capsule network framework to integrate multimodal features for LPI prediction, Capsule-LPI. Capsule-LPI integrates four groups of multimodal features, including sequence features, motif information, physicochemical properties and secondary structure features. Capsule-LPI is composed of four feature-learning subnetworks and one capsule subnetwork. Through comprehensive experimental comparisons and evaluations, we demonstrate that both multimodal features and the architecture of the multichannel capsule network can significantly improve the performance of LPI prediction. The experimental results show that Capsule-LPI performs better than the existing state-of-the-art to

Who reads Capsule-LPI: a LncRNA–protein interaction predicting tool based on a capsule network?

It is typically read by researchers, students, and practitioners in Biochemistry, Genetics and Molecular Biology.

Author
Li, Ying (author);Sun, Hang (author);Feng, Shiyao (author);Zhang, Qi (author);Han, Siyu (author);Du, Wei (author)
Publisher
Springer Science and Business Media LLC
Published
2021
Language
EN
Field
Biochemistry, Genetics and Molecular Biology (Life Sciences)

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