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We have developed a new method, SOAPfuse, to identify fusion transcripts from paired-end RNA-Seq data. SOAPfuse applies an improved partial exhaustion algorithm to construct a library of fusion junction sequences, which can be used to efficiently identify fusion events, and employs a series of filters to nominate high-confidence fusion transcripts. Compared(More)
We demonstrate a generative model that incorporates word-pair connection into the smoothed LDA model to intuitively discover people's wish related activities. The widely used model, LDA topic model, generally generates clusters in the form of separate words. However, this form is not intuitive enough to express people's activities. Therefore, we consider(More)
Mobile grid, based on the integration of the Grid computing and mobile computing, has become a research hotspot in the fields of resources sharing and high performance computing. This paper focuses on the characteristics of mobile grid, establishing the network communication model of mobile grid and keying on the scheduling algorithm in the computing(More)
Climate condition affects users' action and tweet content. We discover that temperature and humidity affects users' action more than the general weather category such as sunny or rainy. In detail, we discover that 9 degree of temperature and 42% of humidity are the best thresholds to affects the change of tweet content.
We propose a method of predicting destinations by using Twitter posts with location information. The proposed method chooses base tweets, which is close to the current user's tweet, and then predict destination using the next set of tweets of base tweet. The base tweets are selected based on not only location closeness but also similarity of tweet content.(More)
We propose a topic model to better estimate activities from tweets. The whole estimation process consists of two phases: one is the cluster generation, and the other is the activity estimation. At the first phase, we obtain the expected trilayer clusters with the components: a topic layer, an activity layer and a word layer. Then, at the second phase, we(More)