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Articles by Xinxin Li
Total Records ( 2 ) for Xinxin Li
  Xinxin Li , Xuan Wang and Muhammad Waqas Anwar
  Strategies of unlabeled data selection are important for semi-supervised learning of natural language processing tasks. To increase the accuracy and diversity of new labeled data, plenty of methods have been proposed, such as ensemble-based self-training, co-training and tri-training methods. In this paper, we propose a simple and effective semi-supervised algorithm for Chinese word segmentation and part-of-speech tagging problem which selects new labeled data agreed by two different approaches: character-based and word-based models. Theoretical and experimental analysis verifies that sentences with same annotation on both models are more accurate than those generated by single models and are suitable for semi-supervised learning as additional data. Experimental results on Chinese Treebank 5.0 demonstrate that our semi-supervised approach is comparable with the best reported semi-supervised approach which employs complex feature engineering.
  Wenqiang Sun , Liang Li , Jiwen Wang , Hehe Liu , Haohan Wang , Xinxin Li , Rongping Zhang and Fang Ding
  MyoD can bind the E-box sequence (CANNTG) in the promoters of downstream muscle target genes such as myogenin thereby regulating their transcription. The expression of myogenic regulatory factors is promoted by transcription of their corresponding genes and post-transcriptional regulation during which RNA-binding proteins have an important role. However, a post-transcriptional modulator of MyoD has not yet been reported. In the present study, a duck eukaryotic expression plasmid pEGFP-N1-MyoD was successfully constructed and expressed in duck myoblasts. After transfection, the number of cells and cellular myogenin expression were significantly increased. Furthermore, the expression of Rbm24 and Rbm38 mRNAs was significantly increased. These results suggest that overexpression of MyoD increased the expression of Rbm24 and Rbm38 during duck myoblast differentiation. These findings lay the foundations for further research of the post-transcriptional regulatory mechanisms of MyoD.
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