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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)
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)
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)
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)
OBJECTIVE There is a clear need to develop biomarkers for Parkinson disease (PD) diagnosis, differential diagnosis of Parkinsonian disorders, and monitoring disease progression. We and others have demonstrated that a decrease in DJ-1 and/or α-synuclein in the cerebrospinal fluid (CSF) is a potential index for Parkinson disease diagnosis, but not for PD(More)
Despite successful treatment of Parkinson's disease (PD) with a wide variety of symptomatic therapy, the disease continues to progress and drug-resistance symptoms become the predominant factors producing the disability of PD patients. Neuroprotective therapies have been tested, but clinically effective drugs have not been found yet. New insights gained(More)