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Institution

Brown University

EducationProvidence, Rhode Island, United States
About: Brown University is a education organization based out in Providence, Rhode Island, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 35778 authors who have published 90896 publications receiving 4471489 citations. The organization is also known as: brown.edu & Brown.


Papers
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Journal ArticleDOI
Thomas Hofmann1
TL;DR: This paper proposes to make use of a temperature controlled version of the Expectation Maximization algorithm for model fitting, which has shown excellent performance in practice, and results in a more principled approach with a solid foundation in statistical inference.
Abstract: This paper presents a novel statistical method for factor analysis of binary and count data which is closely related to a technique known as Latent Semantic Analysis. In contrast to the latter method which stems from linear algebra and performs a Singular Value Decomposition of co-occurrence tables, the proposed technique uses a generative latent class model to perform a probabilistic mixture decomposition. This results in a more principled approach with a solid foundation in statistical inference. More precisely, we propose to make use of a temperature controlled version of the Expectation Maximization algorithm for model fitting, which has shown excellent performance in practice. Probabilistic Latent Semantic Analysis has many applications, most prominently in information retrieval, natural language processing, machine learning from text, and in related areas. The paper presents perplexity results for different types of text and linguistic data collections and discusses an application in automated document indexing. The experiments indicate substantial and consistent improvements of the probabilistic method over standard Latent Semantic Analysis.

2,574 citations

Journal ArticleDOI
04 Jan 2003-BMJ
TL;DR: If medical journals adopt the STARD checklist and flow diagram, the quality of reporting of studies of diagnostic accuracy should improve to the advantage of clinicians, researchers, reviewers, journals, and the public.
Abstract: Objective: To improve the accuracy and completeness of reporting of studies of diagnostic accuracy, to allow readers to assess the potential for bias in a study, and to evaluate a study9s generalisability. Methods: The Standards for Reporting of Diagnostic Accuracy (STARD) steering committee searched the literature to identify publications on the appropriate conduct and reporting of diagnostic studies and extracted potential items into an extensive list. Researchers, editors, and members of professional organisations shortened this list during a two day consensus meeting, with the goal of developing a checklist and a generic flow diagram for studies of diagnostic accuracy. Results: The search for published guidelines about diagnostic research yielded 33 previously published checklists, from which we extracted a list of 75 potential items. At the consensus meeting, participants shortened the list to a 25 item checklist, by using evidence, whenever available. A prototype of a flow diagram provides information about the method of patient recruitment, the order of test execution, and the numbers of patients undergoing the test under evaluation and the reference standard, or both. Conclusions: Evaluation of research depends on complete and accurate reporting. If medical journals adopt the STARD checklist and flow diagram, the quality of reporting of studies of diagnostic accuracy should improve to the advantage of clinicians, researchers, reviewers, journals, and the public. The Standards for Reporting of Diagnostic Accuracy (STARD) steering group aims to improve the accuracy and completeness of reporting of studies of diagnostic accuracy. The group describes and explains the development of a checklist and flow diagram for authors of reports

2,550 citations

Journal ArticleDOI
28 Aug 2013-Nature
TL;DR: Remodelling cellular metabolism constitutes a recurrent pattern in ccRCC that correlates with tumour stage and severity and offers new views on the opportunities for disease treatment.
Abstract: Genetic changes underlying clear cell renal cell carcinoma (ccRCC) include alterations in genes controlling cellular oxygen sensing (for example, VHL) and the maintenance of chromatin states (for example, PBRM1). We surveyed more than 400 tumours using different genomic platforms and identified 19 significantly mutated genes. The PI(3)K/AKT pathway was recurrently mutated, suggesting this pathway as a potential therapeutic target. Widespread DNA hypomethylation was associated with mutation of the H3K36 methyltransferase SETD2, and integrative analysis suggested that mutations involving the SWI/SNF chromatin remodelling complex (PBRM1, ARID1A, SMARCA4) could have far-reaching effects on other pathways. Aggressive cancers demonstrated evidence of a metabolic shift, involving downregulation of genes involved in the TCA cycle, decreased AMPK and PTEN protein levels, upregulation of the pentose phosphate pathway and the glutamine transporter genes, increased acetyl-CoA carboxylase protein, and altered promoter methylation of miR-21 (also known as MIR21) and GRB10. Remodelling cellular metabolism thus constitutes a recurrent pattern in ccRCC that correlates with tumour stage and severity and offers new views on the opportunities for disease treatment.

2,548 citations

Book
01 Jan 2005
TL;DR: Preface 1. Events and probability 2. Discrete random variables and expectation 3. Moments and deviations 4. Chernoff bounds 5. Balls, bins and random graphs 6. Probabilistic method 7. Markov chains and random walks 8. Continuous distributions and the Poisson process
Abstract: Preface 1. Events and probability 2. Discrete random variables and expectation 3. Moments and deviations 4. Chernoff bounds 5. Balls, bins and random graphs 6. The probabilistic method 7. Markov chains and random walks 8. Continuous distributions and the Poisson process 9. Entropy, randomness and information 10. The Monte Carlo method 11. Coupling of Markov chains 12. Martingales 13. Pairwise independence and universal hash functions 14. Balanced allocations References.

2,543 citations

Journal ArticleDOI
09 Dec 1993-Nature
TL;DR: The cloning of complementary DNA encoding an extracellular Ca2+ -sensing receptor from bovine parathyroid is reported with pharmacological and functional properties nearly identical to those of the native receptor.
Abstract: Maintenance of a stable internal environment within complex organisms requires specialized cells that sense changes in the extracellular concentration of specific ions (such as Ca2+). Although the molecular nature of such ion sensors is unknown, parathyroid cells possess a cell surface Ca(2+)-sensing mechanism that also recognizes trivalent and polyvalent cations (such as neomycin) and couples by changes in phosphoinositide turnover and cytosolic Ca2+ to regulation of parathyroid hormone secretion. The latter restores normocalcaemia by acting on kidney and bone. We now report the cloning of complementary DNA encoding an extracellular Ca(2+)-sensing receptor from bovine parathyroid with pharmacological and functional properties nearly identical to those of the native receptor. The novel approximately 120K receptor shares limited similarity with the metabotropic glutamate receptors and features a large extracellular domain, containing clusters of acidic amino-acid residues possibly involved in calcium binding, coupled to a seven-membrane-spanning domain like those in the G-protein-coupled receptor superfamily.

2,542 citations


Authors

Showing all 36143 results

NameH-indexPapersCitations
Walter C. Willett3342399413322
Robert Langer2812324326306
Robert M. Califf1961561167961
Eric J. Topol1931373151025
Joan Massagué189408149951
Joseph Biederman1791012117440
Gonçalo R. Abecasis179595230323
James F. Sallis169825144836
Steven N. Blair165879132929
Charles M. Lieber165521132811
J. S. Lange1602083145919
Christopher J. O'Donnell159869126278
Charles M. Perou156573202951
David J. Mooney15669594172
Richard J. Davidson15660291414
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023126
2022591
20215,549
20205,321
20194,806
20184,462