Institution
Rutgers University
Education•New Brunswick, New Jersey, United States•
About: Rutgers University is a education organization based out in New Brunswick, New Jersey, United States. It is known for research contribution in the topics: Population & Poison control. The organization has 68736 authors who have published 159418 publications receiving 6713860 citations. The organization is also known as: Rutgers, The State University of New Jersey & Rutgers.
Topics: Population, Poison control, Context (language use), Cancer, Gene
Papers published on a yearly basis
Papers
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TL;DR: A complementary DNA for the Aequorea victoria green fluorescent protein produces a fluorescent product when expressed in prokaryotic or eukaryotic cells, which can be used to monitor gene expression and protein localization in living organisms.
Abstract: A complementary DNA for the Aequorea victoria green fluorescent protein (GFP) produces a fluorescent product when expressed in prokaryotic (Escherichia coli) or eukaryotic (Caenorhabditis elegans) cells. Because exogenous substrates and cofactors are not required for this fluorescence, GFP expression can be used to monitor gene expression and protein localization in living organisms.
7,016 citations
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TL;DR: A meta-analysis of the relationships between organizational innovation and 13 potential determinants resulted in statistically significant associations for specialization, functional differencing, and functional differences as mentioned in this paper. But, the authors did not consider the role of organizational innovation in organizational innovation.
Abstract: A meta-analysis of the relationships between organizational innovation and 13 of its potential determinants resulted in statistically significant associations for specialization, functional differe...
6,743 citations
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TL;DR: A unified neural network architecture and learning algorithm that can be applied to various natural language processing tasks including part-of-speech tagging, chunking, named entity recognition, and semantic role labeling is proposed.
Abstract: We propose a unified neural network architecture and learning algorithm that can be applied to various natural language processing tasks including part-of-speech tagging, chunking, named entity recognition, and semantic role labeling. This versatility is achieved by trying to avoid task-specific engineering and therefore disregarding a lot of prior knowledge. Instead of exploiting man-made input features carefully optimized for each task, our system learns internal representations on the basis of vast amounts of mostly unlabeled training data. This work is then used as a basis for building a freely available tagging system with good performance and minimal computational requirements.
6,734 citations
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15 Nov 1996TL;DR: The EM Algorithm and Extensions describes the formulation of the EM algorithm, details its methodology, discusses its implementation, and illustrates applications in many statistical contexts, opening the door to the tremendous potential of this remarkably versatile statistical tool.
Abstract: The first unified account of the theory, methodology, and applications of the EM algorithm and its extensionsSince its inception in 1977, the Expectation-Maximization (EM) algorithm has been the subject of intense scrutiny, dozens of applications, numerous extensions, and thousands of publications. The algorithm and its extensions are now standard tools applied to incomplete data problems in virtually every field in which statistical methods are used. Until now, however, no single source offered a complete and unified treatment of the subject.The EM Algorithm and Extensions describes the formulation of the EM algorithm, details its methodology, discusses its implementation, and illustrates applications in many statistical contexts. Employing numerous examples, Geoffrey McLachlan and Thriyambakam Krishnan examine applications both in evidently incomplete data situations-where data are missing, distributions are truncated, or observations are censored or grouped-and in a broad variety of situations in which incompleteness is neither natural nor evident. They point out the algorithm's shortcomings and explain how these are addressed in the various extensions.Areas of application discussed include: Regression Medical imaging Categorical data analysis Finite mixture analysis Factor analysis Robust statistical modeling Variance-components estimation Survival analysis Repeated-measures designs For theoreticians, practitioners, and graduate students in statistics as well as researchers in the social and physical sciences, The EM Algorithm and Extensions opens the door to the tremendous potential of this remarkably versatile statistical tool.
5,998 citations
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Kevork N. Abazajian1, Jennifer K. Adelman-McCarthy2, Marcel A. Agüeros3, S. Allam4 +220 more•Institutions (77)
TL;DR: A series of improvements to the spectroscopic reductions are described, including better flat fielding and improved wavelength calibration at the blue end, better processing of objects with extremely strong narrow emission lines, and an improved determination of stellar metallicities.
Abstract: This paper describes the Seventh Data Release of the Sloan Digital Sky Survey (SDSS), marking the completion of the original goals of the SDSS and the end of the phase known as SDSS-II. It includes 11,663 deg^2 of imaging data, with most of the ~2000 deg^2 increment over the previous data release lying in regions of low Galactic latitude. The catalog contains five-band photometry for 357 million distinct objects. The survey also includes repeat photometry on a 120° long, 2°.5 wide stripe along the celestial equator in the Southern Galactic Cap, with some regions covered by as many as 90 individual imaging runs. We include a co-addition of the best of these data, going roughly 2 mag fainter than the main survey over 250 deg^2. The survey has completed spectroscopy over 9380 deg^2; the spectroscopy is now complete over a large contiguous area of the Northern Galactic Cap, closing the gap that was present in previous data releases. There are over 1.6 million spectra in total, including 930,000 galaxies, 120,000 quasars, and 460,000 stars. The data release includes improved stellar photometry at low Galactic latitude. The astrometry has all been recalibrated with the second version of the USNO CCD Astrograph Catalog, reducing the rms statistical errors at the bright end to 45 milliarcseconds per coordinate. We further quantify a systematic error in bright galaxy photometry due to poor sky determination; this problem is less severe than previously reported for the majority of galaxies. Finally, we describe a series of improvements to the spectroscopic reductions, including better flat fielding and improved wavelength calibration at the blue end, better processing of objects with extremely strong narrow emission lines, and an improved determination of stellar metallicities.
5,665 citations
Authors
Showing all 69437 results
Name | H-index | Papers | Citations |
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Salim Yusuf | 231 | 1439 | 252912 |
Daniel Levy | 212 | 933 | 194778 |
Eugene V. Koonin | 199 | 1063 | 175111 |
Eric Boerwinkle | 183 | 1321 | 170971 |
David L. Kaplan | 177 | 1944 | 146082 |
Derek R. Lovley | 168 | 582 | 95315 |
Mark Gerstein | 168 | 751 | 149578 |
Gang Chen | 167 | 3372 | 149819 |
Hongfang Liu | 166 | 2356 | 156290 |
Robert Stone | 160 | 1756 | 167901 |
Mark E. Cooper | 158 | 1463 | 124887 |
Michael B. Sporn | 157 | 559 | 94605 |
Cumrun Vafa | 157 | 509 | 88515 |
Wolfgang Wagner | 156 | 2342 | 123391 |
David M. Sabatini | 155 | 413 | 135833 |