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Institution

University of California, Davis

EducationDavis, California, United States
About: University of California, Davis is a education organization based out in Davis, California, United States. It is known for research contribution in the topics: Population & Gene. The organization has 78770 authors who have published 180033 publications receiving 8064158 citations. The organization is also known as: UC Davis & UCD.


Papers
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Journal ArticleDOI
TL;DR: In view of the high death and complication rates of major surgical procedures, surgical safety should now be a substantial global public-health concern.

1,963 citations

Journal ArticleDOI
TL;DR: This study reports a computational method, CEGMA (Core Eukaryotic Genes Mapping Approach), for building a highly reliable set of gene annotations in the absence of experimental data, and defines a set of conserved protein families that occur in a wide range of eukaryotes and presents a mapping procedure that accurately identifies their exon-intron structures in a novel genomic sequence.
Abstract: Motivation The numbers of finished and ongoing genome projects are increasing at a rapid rate, and providing the catalog of genes for these new genomes is a key challenge. Obtaining a set of well-characterized genes is a basic requirement in the initial steps of any genome annotation process. An accurate set of genes is needed in order to learn about species-specific properties, to train gene-finding programs, and to validate automatic predictions. Unfortunately, many new genome projects lack comprehensive experimental data to derive a reliable initial set of genes. Results In this study, we report a computational method, CEGMA (Core Eukaryotic Genes Mapping Approach), for building a highly reliable set of gene annotations in the absence of experimental data. We define a set of conserved protein families that occur in a wide range of eukaryotes, and present a mapping procedure that accurately identifies their exon-intron structures in a novel genomic sequence. CEGMA includes the use of profile-hidden Markov models to ensure the reliability of the gene structures. Our procedure allows one to build an initial set of reliable gene annotations in potentially any eukaryotic genome, even those in draft stages. Availability Software and data sets are available online at http://korflab.ucdavis.edu/Datasets.

1,963 citations

Journal ArticleDOI
D. S. Akerib1, Henrique Araujo2, X. Bai3, A. J. Bailey2, J. Balajthy4, S. Bedikian5, Ethan Bernard5, A. Bernstein6, Alexander Bolozdynya1, A. W. Bradley1, D. Byram7, Sidney Cahn5, M. C. Carmona-Benitez8, C. Chan9, J.J. Chapman9, A. A. Chiller7, C. Chiller7, K. Clark1, T. Coffey1, A. Currie2, A. Curioni5, Steven Dazeley6, L. de Viveiros10, A. Dobi4, J. E. Y. Dobson11, E. M. Dragowsky1, E. Druszkiewicz12, B. N. Edwards5, C. H. Faham13, S. Fiorucci9, C. E. Flores14, R. J. Gaitskell9, V. M. Gehman13, C. Ghag15, K.R. Gibson1, Murdock Gilchriese13, C. R. Hall4, M. Hanhardt3, S. A. Hertel5, M. Horn5, D. Q. Huang9, M. Ihm16, R. G. Jacobsen16, L. Kastens5, K. Kazkaz6, R. Knoche4, S. Kyre8, R. L. Lander14, N. A. Larsen5, C. Lee1, David Leonard4, K. T. Lesko13, A. Lindote10, M.I. Lopes10, A. Lyashenko5, D.C. Malling9, R. L. Mannino17, Daniel McKinsey5, Dongming Mei7, J. Mock14, M. Moongweluwan12, J. A. Morad14, M. Morii18, A. St. J. Murphy11, C. Nehrkorn8, H. N. Nelson8, F. Neves10, James Nikkel5, R. A. Ott14, M. Pangilinan9, P. D. Parker5, E. K. Pease5, K. Pech1, P. Phelps1, L. Reichhart15, T. A. Shutt1, C. Silva10, W. Skulski12, C. Sofka17, V. N. Solovov10, P. Sorensen6, T.M. Stiegler17, K. O'Sullivan5, T. J. Sumner2, Robert Svoboda14, M. Sweany14, Matthew Szydagis14, D. J. Taylor, B. P. Tennyson5, D. R. Tiedt3, Mani Tripathi14, S. Uvarov14, J.R. Verbus9, N. Walsh14, R. C. Webb17, J. T. White17, D. White8, M. S. Witherell8, M. Wlasenko18, F.L.H. Wolfs12, M. Woods14, Chao Zhang7 
TL;DR: The first WIMP search data set is reported, taken during the period from April to August 2013, presenting the analysis of 85.3 live days of data, finding that the LUX data are in disagreement with low-mass W IMP signal interpretations of the results from several recent direct detection experiments.
Abstract: The Large Underground Xenon (LUX) experiment is a dual-phase xenon time-projection chamber operating at the Sanford Underground Research Facility (Lead, South Dakota). The LUX cryostat was filled for the first time in the underground laboratory in February 2013. We report results of the first WIMP search data set, taken during the period from April to August 2013, presenting the analysis of 85.3 live days of data with a fiducial volume of 118 kg. A profile-likelihood analysis technique shows our data to be consistent with the background-only hypothesis, allowing 90% confidence limits to be set on spin-independent WIMP-nucleon elastic scattering with a minimum upper limit on the cross section of 7.6 × 10(-46) cm(2) at a WIMP mass of 33 GeV/c(2). We find that the LUX data are in disagreement with low-mass WIMP signal interpretations of the results from several recent direct detection experiments.

1,962 citations

Journal ArticleDOI
TL;DR: This review presents an overview of the dynamically developing field of mass spectrometry-based metabolomics, a technique that analyzes all detectable analytes in a given sample with subsequent classification of samples and identification of differentially expressed metabolites, which define the sample classes.
Abstract: This review presents an overview of the dynamically developing field of mass spectrometry-based metabolomics. Metabolomics aims at the comprehensive and quantitative analysis of wide arrays of metabolites in biological samples. These numerous analytes have very diverse physico-chemical properties and occur at different abundance levels. Consequently, comprehensive metabolomics investigations are primarily a challenge for analytical chemistry and specifically mass spectrometry has vast potential as a tool for this type of investigation. Metabolomics require special approaches for sample preparation, separation, and mass spectrometric analysis. Current examples of those approaches are described in this review. It primarily focuses on metabolic fingerprinting, a technique that analyzes all detectable analytes in a given sample with subsequent classification of samples and identification of differentially expressed metabolites, which define the sample classes. To perform this complex task, data analysis tools, metabolite libraries, and databases are required. Therefore, recent advances in metabolomics bioinformatics are also discussed.

1,954 citations

Journal ArticleDOI
TL;DR: Investigators in Wuhan, China, describe the spectrum of Covid-19 illness in children under the age of 16 years in SARS-CoV-2 Infection in Children.
Abstract: SARS-CoV-2 Infection in Children In this report, investigators in Wuhan, China, describe the spectrum of Covid-19 illness in children under the age of 16 years. Of 1391 children assessed and tested...

1,945 citations


Authors

Showing all 79538 results

NameH-indexPapersCitations
Eric S. Lander301826525976
Ronald C. Kessler2741332328983
George M. Whitesides2401739269833
Ronald M. Evans199708166722
Virginia M.-Y. Lee194993148820
Scott M. Grundy187841231821
Julie E. Buring186950132967
Patrick O. Brown183755200985
Anil K. Jain1831016192151
John C. Morris1831441168413
Douglas R. Green182661145944
John R. Yates1771036129029
Barry Halliwell173662159518
Roderick T. Bronson169679107702
Hongfang Liu1662356156290
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023262
20221,122
20218,399
20208,661
20198,165
20187,556