Motivation: N4-methylcytosine (4mC) plays an important role in host defense and transcriptional regulation. Accurate identification of 4mc sites provides a more comprehensive understanding of its biological effects. At present, the traditional machine learning algorithms are used in the research on 4mC sites prediction, but the complexity of the algorithms is relatively high, which is not suitable for the processing of large data sets, and the accuracy of prediction needs to be improved. Therefore, it is necessary to develop a new and effective method to accurately identify 4mC sites.Results: In this work, we found a large number of 4mC sites and non 4mC sites of Caenorhabditis elegans (C. elegans) from the latest MethSMRT website, which greatly expanded the dataset of C. elegans, and developed a hybrid deep neural network framework named 4mcDeep-CBI, aiming to identify 4mC sites. In order to obtain the high latitude information of the feature, we input the preliminary extracted features into the Convolutional Neural Network (CNN) and Bidirectional Long Short Term Memory network (BLSTM) to generate advanced features. Taking the advanced features as algorithm input, we have proposed an integrated algorithm to improve feature representation. Experimental results on large new dataset show that the proposed predictor is able to achieve generally better performance in identifying 4mC sites as compared to the state-of-art predictor. Notably, this is the first study of identifying 4mC sites using deep neural network. Moreover, our model runs much faster than the state-of-art predictor.

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Empathy is considered a cornerstone of high-quality health care and a required element of nursing education. Although computer role-playing games (CRPGs) are a promising tool to promote clinical empathy, little is known about how and why it is effective at improving empathy. The goal of the current study is to investigate the feasibility and effectiveness of a CRPG on nursing students' empathy with a focus on immersiveness and perspective. Results from a 2 • 2 (virtual reality [VR] vs. non-VR • patient's family's perspective vs. health care provider's perspective) between-subjects experiment (N = 69) showed that playing the game in VR (vs. non-VR) led to greater spatial presence and empathy. Moreover, playing from the health care provider's (vs. patient's family's) perspective elicited greater empathy. A moderated mediation effect was found, suggesting that users' attention allocation significantly mediated the effect of immersiveness on empathy in the patient's family's perspective condition. These findings show the feasibility of using a role-playing game for nursing education. Both theoretical and practical implications involving empathy training were discussed, along with suggestions for further research.