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—In this paper, we describe PEGASUS, an open source Peta Graph Mining library which performs typical graph mining tasks such as computing the diameter of the graph, computing the radius of each node and finding the connected components. As the size of graphs reaches several Giga-, Tera-or Peta-bytes, the necessity for such a library grows too. To the best(More)
Many data are modeled as tensors, or multi dimensional arrays. Examples include the predicates (subject, verb, object) in knowledge bases, hyperlinks and anchor texts in the Web graphs, sensor streams (time, location, and type), social networks over time, and DBLP conference-author-keyword relations. Tensor decomposition is an important data mining tool(More)
The A9 dopaminergic (DA) neuronal group projecting to the dorsal striatum is the most vulnerable in Parkinson's disease (PD). We genetically engineered mouse embryonic stem (ES) cells to express the transcription factors Nurr1 or Pitx3. After in vitro differentiation of Pitx3-expressing ES cells, the proportion of DA neurons expressing aldehyde(More)
Counting the number of triangles in a graph is a beautiful algorithmic problem which has gained importance over the last years due to its significant role in complex network analysis. Metrics frequently computed such as the clustering coefficient and the transitivity ratio involve the execution of a triangle counting algorithm. Furthermore, several(More)
—Given a real world graph, how should we layout its edges? How can we compress it? These questions are closely related, and the typical approach so far is to find clique-like communities, like the 'cavemen graph', and compress them. We show that the block-diagonal mental image of the 'cavemen graph' is the wrong paradigm, in full agreement with earlier(More)
Given a very large moderate-to-high dimensionality dataset, how could one cluster its points? For datasets that don't fit even on a single disk, parallelism is a first class option. In this paper we explore MapReduce for clustering this kind of data. The main questions are (a) how to minimize the I/O cost, taking into account the already existing data(More)
The neurotransmitter dopamine is integrally involved in the rewarding effects of drugs, and it has also been thought to mediate impulsive behaviors in animal models. Most of the studies of drug effects on impulsive behaviors in humans have involved drugs with complex actions on different transmitter systems and different receptor subtypes. The present study(More)
Biomarkers are urgently needed for the diagnosis and monitoring of disease progression in Parkinson's disease. Both DJ-1 and alpha-synuclein, two proteins critically involved in Parkinson's disease pathogenesis, have been tested as disease biomarkers in several recent studies with inconsistent results. These have been largely due to variation in the protein(More)
Nurr1 is a transcription factor critical for the development of midbrain dopaminergic (DA) neurons. This study modified mouse embryonic stem (ES) cells to constitutively express Nurr1 under the elongation factor-1alpha promoter. The Nurr1-expression in ES cells lead to up-regulation of all DA neuronal markers tested, resulting in about a 4- to 5-fold(More)