Institution
University of North Carolina at Chapel Hill
Education•Chapel Hill, North Carolina, United States•
About: University of North Carolina at Chapel Hill is a education organization based out in Chapel Hill, North Carolina, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 81393 authors who have published 185327 publications receiving 9948508 citations. The organization is also known as: University of North Carolina & North Carolina.
Topics: Population, Poison control, Health care, Cancer, Medicine
Papers published on a yearly basis
Papers
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TL;DR: In this article, the authors propose a method for the identification of the most likely candidate species of a given species from a set of known species: a.k.a. a. nomenclature.
1,466 citations
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24 Oct 2016TL;DR: A novel class of attacks is defined: attacks that are physically realizable and inconspicuous, and allow an attacker to evade recognition or impersonate another individual, and a systematic method to automatically generate such attacks is developed through printing a pair of eyeglass frames.
Abstract: Machine learning is enabling a myriad innovations, including new algorithms for cancer diagnosis and self-driving cars. The broad use of machine learning makes it important to understand the extent to which machine-learning algorithms are subject to attack, particularly when used in applications where physical security or safety is at risk. In this paper, we focus on facial biometric systems, which are widely used in surveillance and access control. We define and investigate a novel class of attacks: attacks that are physically realizable and inconspicuous, and allow an attacker to evade recognition or impersonate another individual. We develop a systematic method to automatically generate such attacks, which are realized through printing a pair of eyeglass frames. When worn by the attacker whose image is supplied to a state-of-the-art face-recognition algorithm, the eyeglasses allow her to evade being recognized or to impersonate another individual. Our investigation focuses on white-box face-recognition systems, but we also demonstrate how similar techniques can be used in black-box scenarios, as well as to avoid face detection.
1,466 citations
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Harvard University1, Massachusetts Institute of Technology2, Broad Institute3, Cardiff University4, University College London5, University of Edinburgh6, Trinity College, Dublin7, Karolinska Institutet8, Uppsala University9, University of Southern California10, University of Aberdeen11, University of North Carolina at Chapel Hill12, QIMR Berghofer Medical Research Institute13, Royal College of Surgeons in Ireland14, National Health Service15, University of Oxford16, Queen Mary University of London17, State University of New York System18, University of Coimbra19
TL;DR: A genome-wide survey of rare CNVs in 3,391 patients with schizophrenia and 3,181 ancestrally matched controls provides strong support for a model of schizophrenia pathogenesis that includes the effects of multiple rare structural variants, both genome- wide and at specific loci.
Abstract: Schizophrenia is a severe mental disorder marked by hallucinations, delusions, cognitive deficits and apathy, with a heritability estimated at 73 - 90% ( ref. 1). Inheritance patterns are complex, and the number and type of genetic variants involved are not understood. Copy number variants ( CNVs) have been identified in individual patients with schizophrenia(2-7) and also in neurodevelopmental disorders(8-11), but large- scale genome- wide surveys have not been performed. Here we report a genome- wide survey of rare CNVs in 3,391 patients with schizophrenia and 3,181 ancestrally matched controls, using high- density microarrays. For CNVs that were observed in less than 1% of the sample and were more than 100 kilobases in length, the total burden is increased 1.15- fold in patients with schizophrenia in comparison with controls. This effect was more pronounced for rarer, single- occurrence CNVs and for those that involved genes as opposed to those that did not. As expected, deletions were found within the region critical for velo- cardio- facial syndrome, which includes psychotic symptoms in 30% of patients(12). Associations with schizophrenia were also found for large deletions on chromosome 15q13.3 and 1q21.1. These associations have not previously been reported, and they remained significant after genome- wide correction. Our results provide strong support for a model of schizophrenia pathogenesis that includes the effects of multiple rare structural variants, both genome- wide and at specific loci.
1,465 citations
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TL;DR: Compared 3,665 US Food and Drug Administration (FDA)-approved and investigational drugs against hundreds of targets, defining each target by its ligands, chemical similarities between drugs and ligand sets predicted thousands of unanticipated associations.
Abstract: Although drugs are intended to be selective, at least some bind to several physiological targets, explaining side effects and efficacy. Because many drug-target combinations exist, it would be useful to explore possible interactions computationally. Here we compared 3,665 US Food and Drug Administration (FDA)-approved and investigational drugs against hundreds of targets, defining each target by its ligands. Chemical similarities between drugs and ligand sets predicted thousands of unanticipated associations. Thirty were tested experimentally, including the antagonism of the beta(1) receptor by the transporter inhibitor Prozac, the inhibition of the 5-hydroxytryptamine (5-HT) transporter by the ion channel drug Vadilex, and antagonism of the histamine H(4) receptor by the enzyme inhibitor Rescriptor. Overall, 23 new drug-target associations were confirmed, five of which were potent (<100 nM). The physiological relevance of one, the drug N,N-dimethyltryptamine (DMT) on serotonergic receptors, was confirmed in a knockout mouse. The chemical similarity approach is systematic and comprehensive, and may suggest side-effects and new indications for many drugs.
1,465 citations
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TL;DR: Treatment of patients with CDI should be stratified depending on whether they have mild-to-moderate, severe, or complicated disease, and a classification of disease severity is proposed to guide therapy that is useful for clinicians.
1,464 citations
Authors
Showing all 82249 results
Name | H-index | Papers | Citations |
---|---|---|---|
Walter C. Willett | 334 | 2399 | 413322 |
Salim Yusuf | 231 | 1439 | 252912 |
David J. Hunter | 213 | 1836 | 207050 |
Irving L. Weissman | 201 | 1141 | 172504 |
Eric J. Topol | 193 | 1373 | 151025 |
Dennis W. Dickson | 191 | 1243 | 148488 |
Scott M. Grundy | 187 | 841 | 231821 |
Peidong Yang | 183 | 562 | 144351 |
Patrick O. Brown | 183 | 755 | 200985 |
Eric Boerwinkle | 183 | 1321 | 170971 |
Alan C. Evans | 183 | 866 | 134642 |
Anil K. Jain | 183 | 1016 | 192151 |
Terrie E. Moffitt | 182 | 594 | 150609 |
Aaron R. Folsom | 181 | 1118 | 134044 |
Valentin Fuster | 179 | 1462 | 185164 |