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Institution

University of California, Santa Cruz

EducationSanta Cruz, California, United States
About: University of California, Santa Cruz is a education organization based out in Santa Cruz, California, United States. It is known for research contribution in the topics: Galaxy & Population. The organization has 15541 authors who have published 44120 publications receiving 2759983 citations. The organization is also known as: UCSC & UC, Santa Cruz.
Topics: Galaxy, Population, Star formation, Redshift, Planet


Papers
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Journal ArticleDOI
TL;DR: The chapter proposes four processes: learning about the outgroup, changed behavior, affective ties, and ingroup reappraisal, and distinguishes between essential and facilitating factors, and emphasizes different outcomes for different stages of contact.
Abstract: Allport specified four conditions for optimal intergroup contact: equal group status within the situation, common goals, intergroup cooperation and authority support. Varied research supports the hypothesis, but four problems remain. 1. A selection bias limits cross-sectional studies, since prejudiced people avoid intergroup contact. Yet research finds that the positive effects of cross-group friendship are larger than those of the bias. 2. Writers overburden the hypothesis with facilitating, but not essential, conditions. 3. The hypothesis fails to address process. The chapter proposes four processes: learning about the outgroup, changed behavior, affective ties, and ingroup reappraisal. 4. The hypothesis does not specify how the effects generalize to other situations, the outgroup or uninvolved outgroups. Acting sequentially, three strategies enhance generalizationodecategorization, salient categorization, and recategorization. Finally, both individual differences and societal norms shape intergroup contact effects. The chapter outlines a longitudinal intergroup contact theory. It distinguishes between essential and facilitating factors, and emphasizes different outcomes for different stages of contact.

4,873 citations

Journal ArticleDOI
Adam J. Bass1, Vesteinn Thorsson2, Ilya Shmulevich2, Sheila Reynolds2  +254 moreInstitutions (32)
11 Sep 2014-Nature
TL;DR: A comprehensive molecular evaluation of 295 primary gastric adenocarcinomas as part of The Cancer Genome Atlas (TCGA) project is described and a molecular classification dividing gastric cancer into four subtypes is proposed.
Abstract: Gastric cancer was the world’s third leading cause of cancer mortality in 2012, responsible for 723,000 deaths1. The vast majority of gastric cancers are adenocarcinomas, which can be further subdivided into intestinal and diffuse types according to the Lauren classification2. An alternative system, proposed by the World Health Organization, divides gastric cancer into papillary, tubular, mucinous (colloid) and poorly cohesive carcinomas3. These classification systems have little clinical utility, making the development of robust classifiers that can guide patient therapy an urgent priority. The majority of gastric cancers are associated with infectious agents, including the bacterium Helicobacter pylori4 and Epstein–Barr virus (EBV). The distribution of histological subtypes of gastric cancer and the frequencies of H. pylori and EBV associated gastric cancer vary across the globe5. A small minority of gastric cancer cases are associated with germline mutation in E-cadherin (CDH1)6 or mismatch repair genes7 (Lynch syndrome), whereas sporadic mismatch repair-deficient gastric cancers have epigenetic silencing of MLH1 in the context of a CpG island methylator phenotype (CIMP)8. Molecular profiling of gastric cancer has been performed using gene expression or DNA sequencing9–12, but has not led to a clear biologic classification scheme. The goals of this study by The Cancer Genome Atlas (TCGA) were to develop a robust molecular classification of gastric cancer and to identify dysregulated pathways and candidate drivers of distinct classes of gastric cancer.

4,583 citations

Journal ArticleDOI
18 Oct 2007-Nature
TL;DR: The Phase II HapMap is described, which characterizes over 3.1 million human single nucleotide polymorphisms genotyped in 270 individuals from four geographically diverse populations and includes 25–35% of common SNP variation in the populations surveyed, and increased differentiation at non-synonymous, compared to synonymous, SNPs is demonstrated.
Abstract: We describe the Phase II HapMap, which characterizes over 3.1 million human single nucleotide polymorphisms (SNPs) genotyped in 270 individuals from four geographically diverse populations and includes 25-35% of common SNP variation in the populations surveyed. The map is estimated to capture untyped common variation with an average maximum r2 of between 0.9 and 0.96 depending on population. We demonstrate that the current generation of commercial genome-wide genotyping products captures common Phase II SNPs with an average maximum r2 of up to 0.8 in African and up to 0.95 in non-African populations, and that potential gains in power in association studies can be obtained through imputation. These data also reveal novel aspects of the structure of linkage disequilibrium. We show that 10-30% of pairs of individuals within a population share at least one region of extended genetic identity arising from recent ancestry and that up to 1% of all common variants are untaggable, primarily because they lie within recombination hotspots. We show that recombination rates vary systematically around genes and between genes of different function. Finally, we demonstrate increased differentiation at non-synonymous, compared to synonymous, SNPs, resulting from systematic differences in the strength or efficacy of natural selection between populations.

4,565 citations

Journal ArticleDOI
Kaoru Hagiwara, Ken Ichi Hikasa1, Koji Nakamura, Masaharu Tanabashi1, M. Aguilar-Benitez, Claude Amsler2, R. M. Barnett3, P. R. Burchat4, C. D. Carone5, C. Caso6, G. Conforto7, Olav Dahl3, Michael Doser8, Semen Eidelman9, Jonathan L. Feng10, L. K. Gibbons11, M. C. Goodman12, Christoph Grab13, D. E. Groom3, Atul Gurtu8, Atul Gurtu14, K. G. Hayes15, J.J. Hernández-Rey16, K. Honscheid17, Christopher Kolda18, Michelangelo L. Mangano8, D. M. Manley19, Aneesh V. Manohar20, John March-Russell8, Alberto Masoni, Ramon Miquel3, Klaus Mönig, Hitoshi Murayama21, Hitoshi Murayama3, S. Sánchez Navas13, Keith A. Olive22, Luc Pape8, C. Patrignani6, A. Piepke23, Matts Roos24, John Terning25, Nils A. Tornqvist24, T. G. Trippe3, Petr Vogel26, C. G. Wohl3, Ron L. Workman27, W-M. Yao3, B. Armstrong3, P. S. Gee3, K. S. Lugovsky, S. B. Lugovsky, V. S. Lugovsky, Marina Artuso28, D. Asner29, K. S. Babu30, E. L. Barberio8, Marco Battaglia8, H. Bichsel31, O. Biebel32, P. Bloch8, Robert N. Cahn3, Ariella Cattai8, R.S. Chivukula33, R. Cousins34, G. A. Cowan35, Thibault Damour36, K. Desler, R. J. Donahue3, D. A. Edwards, Victor Daniel Elvira37, Jens Erler38, V. V. Ezhela, A Fassò8, W. Fetscher13, Brian D. Fields39, B. Foster40, Daniel Froidevaux8, Masataka Fukugita41, Thomas K. Gaisser42, L. A. Garren37, H J Gerber13, Frederick J. Gilman43, Howard E. Haber44, C. A. Hagmann29, J.L. Hewett4, Ian Hinchliffe3, Craig J. Hogan31, G. Höhler45, P. Igo-Kemenes46, John David Jackson3, Kurtis F Johnson47, D. Karlen48, B. Kayser37, S. R. Klein3, Konrad Kleinknecht49, I.G. Knowles50, P. Kreitz4, Yu V. Kuyanov, R. Landua8, Paul Langacker38, L. S. Littenberg51, Alan D. Martin52, Tatsuya Nakada8, Tatsuya Nakada53, Meenakshi Narain33, Paolo Nason, John A. Peacock54, H. R. Quinn55, Stuart Raby17, Georg G. Raffelt32, E. A. Razuvaev, B. Renk49, L. Rolandi8, Michael T Ronan3, L.J. Rosenberg54, C.T. Sachrajda55, A. I. Sanda56, Subir Sarkar57, Michael Schmitt58, O. Schneider53, Douglas Scott59, W. G. Seligman60, M. H. Shaevitz60, Torbjörn Sjöstrand61, George F. Smoot3, Stefan M Spanier4, H. Spieler3, N. J. C. Spooner62, Mark Srednicki63, Achim Stahl, Todor Stanev42, M. Suzuki3, N. P. Tkachenko, German Valencia64, K. van Bibber29, Manuella Vincter65, D. R. Ward66, Bryan R. Webber66, M R Whalley52, Lincoln Wolfenstein43, J. Womersley37, C. L. Woody51, Oleg Zenin 
Tohoku University1, University of Zurich2, Lawrence Berkeley National Laboratory3, Stanford University4, College of William & Mary5, University of Genoa6, University of Urbino7, CERN8, Budker Institute of Nuclear Physics9, University of California, Irvine10, Cornell University11, Argonne National Laboratory12, ETH Zurich13, Tata Institute of Fundamental Research14, Hillsdale College15, Spanish National Research Council16, Ohio State University17, University of Notre Dame18, Kent State University19, University of California, San Diego20, University of California, Berkeley21, University of Minnesota22, University of Alabama23, University of Helsinki24, Los Alamos National Laboratory25, California Institute of Technology26, George Washington University27, Syracuse University28, Lawrence Livermore National Laboratory29, Oklahoma State University–Stillwater30, University of Washington31, Max Planck Society32, Boston University33, University of California, Los Angeles34, Royal Holloway, University of London35, Université Paris-Saclay36, Fermilab37, University of Pennsylvania38, University of Illinois at Urbana–Champaign39, University of Bristol40, University of Tokyo41, University of Delaware42, Carnegie Mellon University43, University of California, Santa Cruz44, Karlsruhe Institute of Technology45, Heidelberg University46, Florida State University47, Carleton University48, University of Mainz49, University of Edinburgh50, Brookhaven National Laboratory51, Durham University52, University of Lausanne53, Massachusetts Institute of Technology54, University of Southampton55, Nagoya University56, University of Oxford57, Northwestern University58, University of British Columbia59, Columbia University60, Lund University61, University of Sheffield62, University of California, Santa Barbara63, Iowa State University64, University of Alberta65, University of Cambridge66
TL;DR: The Particle Data Group's biennial review as mentioned in this paper summarizes much of particle physics, using data from previous editions, plus 2658 new measurements from 644 papers, and lists, evaluates, and average measured properties of gauge bosons, leptons, quarks, mesons, and baryons.
Abstract: This biennial Review summarizes much of particle physics. Using data from previous editions, plus 2658 new measurements from 644 papers, we list, evaluate, and average measured properties of gauge bosons, leptons, quarks, mesons, and baryons. We summarize searches for hypothetical particles such as Higgs bosons, heavy neutrinos, and supersymmetric particles. All the particle properties and search limits are listed in Summary Tables. We also give numerous tables, figures, formulae, and reviews of topics such as the Standard Model, particle detectors, probability, and statistics. Among the 112 reviews are many that are new or heavily revised including those on Heavy-Quark and Soft-Collinear Effective Theory, Neutrino Cross Section Measurements, Monte Carlo Event Generators, Lattice QCD, Heavy Quarkonium Spectroscopy, Top Quark, Dark Matter, V-cb & V-ub, Quantum Chromodynamics, High-Energy Collider Parameters, Astrophysical Constants, Cosmological Parameters, and Dark Matter. A booklet is available containing the Summary Tables and abbreviated versions of some of the other sections of this full Review. All tables, listings, and reviews (and errata) are also available on the Particle Data Group website: http://pdg.lbl.gov.

4,465 citations

Journal ArticleDOI
TL;DR: This work has examined the completeness of the transcript annotation and found that 35% of transcriptional start sites are supported by CAGE clusters and 62% of protein-coding genes have annotated polyA sites, and over one-third of GENCODE protein-Coding genes aresupported by peptide hits derived from mass spectrometry spectra submitted to Peptide Atlas.
Abstract: The GENCODE Consortium aims to identify all gene features in the human genome using a combination of computational analysis, manual annotation, and experimental validation. Since the first public release of this annotation data set, few new protein-coding loci have been added, yet the number of alternative splicing transcripts annotated has steadily increased. The GENCODE 7 release contains 20,687 protein-coding and 9640 long noncoding RNA loci and has 33,977 coding transcripts not represented in UCSC genes and RefSeq. It also has the most comprehensive annotation of long noncoding RNA (lncRNA) loci publicly available with the predominant transcript form consisting of two exons. We have examined the completeness of the transcript annotation and found that 35% of transcriptional start sites are supported by CAGE clusters and 62% of protein-coding genes have annotated polyA sites. Over one-third of GENCODE protein-coding genes are supported by peptide hits derived from mass spectrometry spectra submitted to Peptide Atlas. New models derived from the Illumina Body Map 2.0 RNA-seq data identify 3689 new loci not currently in GENCODE, of which 3127 consist of two exon models indicating that they are possibly unannotated long noncoding loci. GENCODE 7 is publicly available from gencodegenes.org and via the Ensembl and UCSC Genome Browsers.

4,281 citations


Authors

Showing all 15733 results

NameH-indexPapersCitations
David J. Schlegel193600193972
David R. Williams1782034138789
John R. Yates1771036129029
David Haussler172488224960
Evan E. Eichler170567150409
Anton M. Koekemoer1681127106796
Mark Gerstein168751149578
Alexander S. Szalay166936145745
Charles M. Lieber165521132811
Jorge E. Cortes1632784124154
M. Razzano155515106357
Lars Hernquist14859888554
Aaron Dominguez1471968113224
Taeghwan Hyeon13956375814
Garth D. Illingworth13750561793
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
202351
2022328
20212,157
20202,353
20192,209
20182,157