Institution
Stony Brook University
Education•Stony Brook, New York, United States•
About: Stony Brook University is a education organization based out in Stony Brook, New York, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 32534 authors who have published 68218 publications receiving 3035131 citations. The organization is also known as: State University of New York at Stony Brook & SUNY Stony Brook.
Papers published on a yearly basis
Papers
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TL;DR: This survey aims to provide a general, comprehensive, and structured overview of the state-of-the-art methods for anomaly detection in data represented as graphs, and gives a general framework for the algorithms categorized under various settings.
Abstract: Detecting anomalies in data is a vital task, with numerous high-impact applications in areas such as security, finance, health care, and law enforcement. While numerous techniques have been developed in past years for spotting outliers and anomalies in unstructured collections of multi-dimensional points, with graph data becoming ubiquitous, techniques for structured graph data have been of focus recently. As objects in graphs have long-range correlations, a suite of novel technology has been developed for anomaly detection in graph data. This survey aims to provide a general, comprehensive, and structured overview of the state-of-the-art methods for anomaly detection in data represented as graphs. As a key contribution, we give a general framework for the algorithms categorized under various settings: unsupervised versus (semi-)supervised approaches, for static versus dynamic graphs, for attributed versus plain graphs. We highlight the effectiveness, scalability, generality, and robustness aspects of the methods. What is more, we stress the importance of anomaly attribution and highlight the major techniques that facilitate digging out the root cause, or the `why', of the detected anomalies for further analysis and sense-making. Finally, we present several real-world applications of graph-based anomaly detection in diverse domains, including financial, auction, computer traffic, and social networks. We conclude our survey with a discussion on open theoretical and practical challenges in the field.
998 citations
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TL;DR: This article evaluated the ability of CEMs to predict species distributions under different climates by comparing their predictions with those obtained with a mechanistic model (MM), in which the distribution of a species is modeled based on knowledge of the species' physiology and the potential distributions of 100 plant species were modeled with an MM for current conditions, a past climate reconstruction (21000 years before present) and a future climate projection (double preindustrial CO2 conditions).
Abstract: Climate envelope models (CEMs) have been used to predict the distribution of species under current, past, and future climatic conditions by inferring a species’ environmental requirements from localities where it is currently known to occur. CEMs can be evaluated for their ability to predict current species distributions but it is unclear whether models that are successful in predicting current distributions are equally successful in predicting distributions under different climates (i.e. different regions or time periods). We evaluated the ability of CEMs to predict species distributions under different climates by comparing their predictions with those obtained with a mechanistic model (MM). In an MM the distribution of a species is modeled based on knowledge of a species’ physiology. The potential distributions of 100 plant species were modeled with an MM for current conditions, a past climate reconstruction (21000 years before present) and a future climate projection (double preindustrial CO2 conditions). Point localities extracted from the currently suitable area according to the MM were used to predict current, future, and past distributions with four CEMs covering a broad range of statistical approaches: Bioclim (percentile distributions), Domain (distance metric), GAM (general additive modeling), and Maxent (maximum entropy). Domain performed very poorly, strongly underestimating range sizes for past or future conditions. Maxent and GAM performed as well under current climates as under past and future climates. Bioclim slightly underestimated range sizes but the predicted ranges overlapped more with the ranges predicted with the MM than those predicted with GAM did. Ranges predicted with Maxent overlapped most with those produced with the MMs, but compared with the ranges predicted with GAM they were more variable and sometimes much too large. Our results suggest that some CEMs can indeed be used to predict species distributions under climate change, but individual modeling approaches should be validated for this purpose, and model choice could be made dependent on the purpose of a particular study.
985 citations
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TL;DR: A reflection on the results indicates that HA coatings can promote earlier and stronger fixation but exhibit a durability that can be related to the coating quality.
Abstract: The clinical use of plasma-sprayed hydroxyapatite (HA) coatings on metal implants has aroused as many controversies as interests over the last decade. Although faster and stronger fixation and more bone growth have been revealed, the performance of HA-coated implants has been doubted. This article will initially address the fundamentals of the material selection, design, and processing of the HA coating and show how the coating microstructure and properties can be a good predictor of the expected behavior in the body. Further discussion will clarify the major concerns with the clinical use of HA coatings and introduce a comprehensive review concerning the outcomes experienced with respect to clinical practice over the past 5 years. A reflection on the results indicates that HA coatings can promote earlier and stronger fixation but exhibit a durability that can be related to the coating quality. Specific relationships between coating quality and clinical performance are being established as characterization methods disclose more information about the coating.
985 citations
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Yale University1, Stanford University2, University of Toronto3, Harvard University4, University of California, Santa Cruz5, University of North Carolina at Chapel Hill6, Ontario Institute for Cancer Research7, New York University8, Stony Brook University9, University of Cambridge10, Hoffmann-La Roche11, Lawrence Berkeley National Laboratory12, University of California, San Diego13, Rockefeller University14, University of Washington15, National Institutes of Health16, University of Michigan17, Fred Hutchinson Cancer Research Center18, Max Planck Society19, Memorial Sloan Kettering Cancer Center20, Weizmann Institute of Science21, Max Delbrück Center for Molecular Medicine22, Cold Spring Harbor Laboratory23, Vanderbilt University24, New York University Abu Dhabi25
TL;DR: These studies identified regions of the nematode and fly genomes that show highly occupied targets (or HOT) regions where DNA was bound by more than 15 of the transcription factors analyzed and the expression of related genes were characterized, providing insights into the organization, structure, and function of the two genomes.
Abstract: We systematically generated large-scale data sets to improve genome annotation for the nematode Caenorhabditis elegans, a key model organism. These data sets include transcriptome profiling across a developmental time course, genome-wide identification of transcription factor-binding sites, and maps of chromatin organization. From this, we created more complete and accurate gene models, including alternative splice forms and candidate noncoding RNAs. We constructed hierarchical networks of transcription factor-binding and microRNA interactions and discovered chromosomal locations bound by an unusually large number of transcription factors. Different patterns of chromatin composition and histone modification were revealed between chromosome arms and centers, with similarly prominent differences between autosomes and the X chromosome. Integrating data types, we built statistical models relating chromatin, transcription factor binding, and gene expression. Overall, our analyses ascribed putative functions to most of the conserved genome.
978 citations
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TL;DR: Positive behavior support (PBS) is an applied science that uses educational and systems change methods (environmental redesign) to enhance quality of life and minimize problem behavior as discussed by the authors.
Abstract: Positive behavior support (PBS) is an applied science that uses educational and systems change methods (environmental redesign) to enhance quality of life and minimize problem behavior. PBS initial...
977 citations
Authors
Showing all 32829 results
Name | H-index | Papers | Citations |
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Zhong Lin Wang | 245 | 2529 | 259003 |
Dennis W. Dickson | 191 | 1243 | 148488 |
Hyun-Chul Kim | 176 | 4076 | 183227 |
David Baker | 173 | 1226 | 109377 |
J. N. Butler | 172 | 2525 | 175561 |
Roderick T. Bronson | 169 | 679 | 107702 |
Nora D. Volkow | 165 | 958 | 107463 |
Jovan Milosevic | 152 | 1433 | 106802 |
Thomas E. Starzl | 150 | 1625 | 91704 |
Paolo Boffetta | 148 | 1455 | 93876 |
Jacques Banchereau | 143 | 634 | 99261 |
Larry R. Squire | 143 | 472 | 85306 |
John D. E. Gabrieli | 142 | 480 | 68254 |
Alexander Milov | 142 | 1143 | 93374 |
Meenakshi Narain | 142 | 1805 | 147741 |