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Frequent pattern mining has been a focused theme in data mining research for over a decade. Abundant literature has been dedicated to this research and tremendous progress has been made, ranging from efficient and scalable algorithms for frequent itemset mining in transaction databases to numerous research frontiers, such as sequential pattern mining,(More)
The goal of graph clustering is to partition vertices in a large graph into different clusters based on various criteria such as vertex con-nectivity or neighborhood similarity. Graph clustering techniques are very useful for detecting densely connected groups in a large graph. Many existing graph clustering methods mainly focus on the topological structure(More)
Graph-based semi-supervised learning has gained considerable interests in the past several years thanks to its effectiveness in combining labeled and unlabeled data through label propagation for better object modeling and classification. A critical issue in constructing a graph is the weight assignment where the weight of an edge specifies the similarity(More)
Centrosome- and cilia-associated proteins play crucial roles in establishing polarity and regulating intracellular transport in post-mitotic cells. Using genetic mapping and positional candidate strategy, we have identified an in-frame deletion in a novel centrosomal protein CEP290 (also called NPHP6), leading to early-onset retinal degeneration in a newly(More)
The application of frequent patterns in classification appeared in sporadic studies and achieved initial success in the classification of relational data, text documents and graphs. In this paper, we conduct a systematic exploration of frequent pattern-based classification, and provide solid reasons supporting this methodology. It was well known that(More)
Many real life sequence databases grow incrementally. It is undesirable to mine sequential patterns from scratch each time when a small set of sequences grow, or when some new sequences are added into the database. Incremental algorithm should be developed for sequential pattern mining so that mining can be adapted to incremental database updates. However,(More)
Pre-mRNAs undergo splicing to remove introns, and the spliced mRNA is exported to the cytoplasm for translation. Here we investigated the mechanism for recruitment of the conserved mRNA export machinery (TREX complex) to mRNA. We show that the human TREX complex is recruited to a region near the 5' end of mRNA, with the TREX component Aly bound closest to(More)
Frequent-pattern mining has been studied extensively on scalable methods for mining various kinds of patterns including itemsets, sequences, and graphs. However, the bottleneck of frequent-pattern mining is not at the efficiency but at the interpretability, due to the huge number of patterns generated by the mining process.In this paper, we examine how to(More)
Bug localization has attracted a lot of attention recently. Most existing methods focus on pinpointing a single statement or function call which is very likely to contain bugs. Although such methods could be very accurate, it is usually very hard for developers to understand the context of the bug, given each bug location in isolation. In this study, we(More)