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Methods for efficient mining of frequent patterns have been studied extensively by many researchers. However, the previously proposed methods still encounter some performance bottlenecks when mining databases with different data characteristics, such as dense vs. sparse, long vs. short patterns, memory-based vs. disk-based, etc. In this study, we propose a(More)
BACKGROUND Protein-carbohydrate interactions are believed to be important in many biological processes that involve cell-cell communication. Apart from the selectins, the only well-characterized vertebrate sialic acid-dependent adhesion molecules are CD22 and sialoadhesin; CD22 is a member of the immunoglobulin superfamily that is expressed by B lymphocytes(More)
Myelin-associated glycoprotein (MAG) is a potent inhibitor of axonal regeneration from both cerebellar neurons and adult dorsal root ganglion (DRG) neurons. In contrast, MAG promotes axonal growth from newborn DRG neurons. Here, we show that the switch in response to MAG from promotion to inhibition of neurite outgrowth by DRg neurons occurs sharply at(More)
Myelin-associated glycoprotein (MAG) is a potent inhibitor of axonal regeneration when used as a substrate for growth. However, to be characterized definitively as inhibitory rather than nonpermissive, MAG must also inhibit axonal regeneration when presented in solution. Here, we show that soluble dMAG (extracellular domain only), released in abundance from(More)
The adult, mammalian CNS does not regenerate after injury largely because of a glial scar and inhibitors of regeneration in myelin. To date, two myelin inhibitors, myelin-associated glycoprotein (MAG) and Nogo, both transmembrane proteins, have been identified. No secreted inhibitors of regeneration have been described. However, a proteolytic fragment of(More)
JIAN PEI1,∗, JIAWEI HAN2, HONGJUN LU3,†, SHOJIRO NISHIO4, SHIWEI TANG5 and DONGQING YANG5 1School of Computing Science, Simon Fraser University, Burnaby, BC, Canada V5A 1S6 E-mail: jpei@cs.sfu.ca 2University of Illinois Urbana, IL 61801, USA E-mail: hanj@cs.uiuc.edu 3Hong Kong University of Science and Technology, Hong Kong 4Osaka University, Osaka, Japan(More)
Density-based clustering is a sort of clustering analysis methods, which can discover clusters with arbitrary shape and is insensitive to noise data. The efficiency of data mining algorithms is strongly needed with data becoming larger and larger. In this paper, we present a new fast clustering algorithm called CURD, which means Clustering Using References(More)