Predicting lncRNA-disease associations with network based message passing | IEEE Conference Publication | IEEE Xplore

Predicting lncRNA-disease associations with network based message passing


Abstract:

The increasing number of studies have shown that lncRNAs are involved in various biological processes and play crucial roles in many complex human diseases. The small-siz...Show More

Abstract:

The increasing number of studies have shown that lncRNAs are involved in various biological processes and play crucial roles in many complex human diseases. The small-size of validated lncRNA-disease associations creates a pressing demand to develop effective computational methods for inferring potential associations. However, most of existing methods suffer from the insufficiency of embedding representations, namely they merely extract features of lncRNAs and diseases from themselves, while leave out the rich information contained in their neighbors. In this paper, we propose a network based representation learning method that extracts high-level features from a node as well as its neighborhood to predict associations between lncRNAs and diseases. Firstly, we construct the lncRNA-disease network by taking lncRNA/disease similarities and lncRNA-disease associations into account. And then, we build the initial embedding of a lncRNA (a disease) with the combination of one-hot vector and probability vector. Subsequently, we utilize message passing on the network and augment the embedding of a lncRNA (a disease) by capturing messages propagated from its neighbor nodes. Finally, we predict lncRNA-disease associations based on representations that are not only from themselves but also propagated from neighbors. To generate a balanced training dataset, we select reliable negative examples from unlabeled samples. Experimental results show that our approach can achieve better performance than other existing methods.
Date of Conference: 09-12 December 2021
Date Added to IEEE Xplore: 14 January 2022
ISBN Information:
Conference Location: Houston, TX, USA

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