Institution
University of Massachusetts Amherst
Education•Amherst Center, Massachusetts, United States•
About: University of Massachusetts Amherst is a education organization based out in Amherst Center, Massachusetts, United States. It is known for research contribution in the topics: Population & Galaxy. The organization has 37274 authors who have published 83965 publications receiving 3834996 citations. The organization is also known as: UMass Amherst & Massachusetts State College.
Papers published on a yearly basis
Papers
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01 Jan 19731,361 citations
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TL;DR: A specific enrichment of microorganisms of the family Geobacteraceae is reported on energy-harvesting anodes, and it is shown that these microorganisms can conserve energy to support their growth by oxidizing organic compounds with an electrode serving as the sole electron acceptor.
Abstract: Energy in the form of electricity can be harvested from marine sediments by placing a graphite electrode (the anode) in the anoxic zone and connecting it to a graphite cathode in the overlying aerobic water. We report a specific enrichment of microorganisms of the family Geobacteraceae on energy-harvesting anodes, and we show that these microorganisms can conserve energy to support their growth by oxidizing organic compounds with an electrode serving as the sole electron acceptor. This finding not only provides a method for extracting energy from organic matter, but also suggests a strategy for promoting the bioremediation of organic contaminants in subsurface environments.
1,356 citations
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George Washington University1, Seattle Biomed2, University of Washington3, J. Craig Venter Institute4, Karolinska Institutet5, University of California, Los Angeles6, Universidade Federal de Minas Gerais7, Uppsala University8, Centre national de la recherche scientifique9, University of Glasgow10, University of Cambridge11, Federal University of São Paulo12, Children's Hospital Oakland Research Institute13, Johns Hopkins University School of Medicine14, National Research Council15, University of Oxford16, University of London17, University of Massachusetts Amherst18, Oswaldo Cruz Foundation19, University of Buenos Aires20, Central University of Venezuela21, National University of Singapore22, University of Georgia23
TL;DR: Although the Tritryp lack several classes of signaling molecules, their kinomes contain a large and diverse set of protein kinases and phosphatases; their size and diversity imply previously unknown interactions and regulatory processes, which may be targets for intervention.
Abstract: Whole-genome sequencing of the protozoan pathogen Trypanosoma cruzi revealed that the diploid genome contains a predicted 22,570 proteins encoded by genes, of which 12,570 represent allelic pairs. Over 50% of the genome consists of repeated sequences, such as retrotransposons and genes for large families of surface molecules, which include trans-sialidases, mucins, gp63s, and a large novel family (>1300 copies) of mucin-associated surface protein (MASP) genes. Analyses of the T. cruzi, T. brucei, and Leishmania major (Tritryp) genomes imply differences from other eukaryotes in DNA repair and initiation of replication and reflect their unusual mitochondrial DNA. Although the Tritryp lack several classes of signaling molecules, their kinomes contain a large and diverse set of protein kinases and phosphatases; their size and diversity imply previously unknown interactions and regulatory processes, which may be targets for intervention.
1,349 citations
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18 Aug 1996TL;DR: It is shown that, although global analysis haa some advantages, local analysia is generally more effective than global techniques and using global analysis techniques.
Abstract: Automatic query expansion has long been suggested as a technique for dealing with the fundamental issue of word mismatch in information retrieval. A number of approaches to expansion have been studied and, more recently, attention has focused on techniques that analyze the corpus to discover word relationship (global techniques) and those that analyze documents retrieved by the initial query ( local feedback). In this paper, we compare the effectiveness of these approaches and show that, although global analysis haa some advantages, local analysia is generally more effective. We also show that using global analysis techniques.
1,341 citations
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27 Jul 2011TL;DR: A novel statistical topic model based on an automated evaluation metric based on this metric that significantly improves topic quality in a large-scale document collection from the National Institutes of Health (NIH).
Abstract: Latent variable models have the potential to add value to large document collections by discovering interpretable, low-dimensional subspaces. In order for people to use such models, however, they must trust them. Unfortunately, typical dimensionality reduction methods for text, such as latent Dirichlet allocation, often produce low-dimensional subspaces (topics) that are obviously flawed to human domain experts. The contributions of this paper are threefold: (1) An analysis of the ways in which topics can be flawed; (2) an automated evaluation metric for identifying such topics that does not rely on human annotators or reference collections outside the training data; (3) a novel statistical topic model based on this metric that significantly improves topic quality in a large-scale document collection from the National Institutes of Health (NIH).
1,339 citations
Authors
Showing all 37601 results
Name | H-index | Papers | Citations |
---|---|---|---|
George M. Whitesides | 240 | 1739 | 269833 |
Joan Massagué | 189 | 408 | 149951 |
David H. Weinberg | 183 | 700 | 171424 |
David L. Kaplan | 177 | 1944 | 146082 |
Michael I. Jordan | 176 | 1016 | 216204 |
James F. Sallis | 169 | 825 | 144836 |
Bradley T. Hyman | 169 | 765 | 136098 |
Anton M. Koekemoer | 168 | 1127 | 106796 |
Derek R. Lovley | 168 | 582 | 95315 |
Michel C. Nussenzweig | 165 | 516 | 87665 |
Alfred L. Goldberg | 156 | 474 | 88296 |
Donna Spiegelman | 152 | 804 | 85428 |
Susan E. Hankinson | 151 | 789 | 88297 |
Bernard Moss | 147 | 830 | 76991 |
Roger J. Davis | 147 | 498 | 103478 |