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Institution

Stanford University

EducationStanford, California, United States
About: Stanford University is a(n) education organization based out in Stanford, California, United States. It is known for research contribution in the topic(s): Population & Transplantation. The organization has 125751 authors who have published 320347 publication(s) receiving 21892059 citation(s). The organization is also known as: Leland Stanford Junior University & University of Stanford.
Topics: Population, Transplantation, Cancer, Gene, Health care
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D.L. Donoho1
01 Jan 2004-
TL;DR: It is possible to design n=O(Nlog(m)) nonadaptive measurements allowing reconstruction with accuracy comparable to that attainable with direct knowledge of the N most important coefficients, and a good approximation to those N important coefficients is extracted from the n measurements by solving a linear program-Basis Pursuit in signal processing.
Abstract: Suppose x is an unknown vector in Ropfm (a digital image or signal); we plan to measure n general linear functionals of x and then reconstruct. If x is known to be compressible by transform coding with a known transform, and we reconstruct via the nonlinear procedure defined here, the number of measurements n can be dramatically smaller than the size m. Thus, certain natural classes of images with m pixels need only n=O(m1/4log5/2(m)) nonadaptive nonpixel samples for faithful recovery, as opposed to the usual m pixel samples. More specifically, suppose x has a sparse representation in some orthonormal basis (e.g., wavelet, Fourier) or tight frame (e.g., curvelet, Gabor)-so the coefficients belong to an lscrp ball for 0

18,593 citations


Journal ArticleDOI
Abstract: The present article presents an integrative theoretical framework to explain and to predict psychological changes achieved by different modes of treatment. This theory states that psychological procedures, whatever their form, alter the level and strength of self-efficacy. It is hypothesized that expectations of personal efficacy determine whether coping behavior will be initiated, how much effort will be expended, and how long it will be sustained in the face of obstacles and aversive experiences. Persistence in activities that are subjectively threatening but in fact relatively safe produces, through experiences of mastery, further enhancement of self-efficacy and corresponding reductions in defensive behavior. In the proposed model, expectations of personal efficacy are derived from four principal sources of information: performance accomplishments, vicarious experience, verbal persuasion, and physiological states. The more dependable the experiential sources, the greater are the changes in perceived selfefficacy. A number of factors are identified as influencing the cognitive processing of efficacy information arising from enactive, vicarious, exhortative, and emotive sources. The differential power of diverse therapeutic procedures is analyzed in terms of the postulated cognitive mechanism of operation. Findings are reported from microanalyses of enactive, vicarious, and emotive modes of treatment that support the hypothesized relationship between perceived self-efficacy and behavioral changes. Possible directions for further research are discussed.

16,650 citations


Journal ArticleDOI
S. Agostinelli1, John Allison2, K. Amako3, J. Apostolakis4, Henrique Araujo5, P. Arce4, Makoto Asai6, D. Axen4, S. Banerjee7, G. Barrand, F. Behner4, Lorenzo Bellagamba8, J. Boudreau9, L. Broglia10, A. Brunengo8, H. Burkhardt4, Stephane Chauvie, J. Chuma11, R. Chytracek4, Gene Cooperman12, G. Cosmo4, P. V. Degtyarenko13, Andrea Dell'Acqua4, G. Depaola14, D. Dietrich15, R. Enami, A. Feliciello, C. Ferguson16, H. Fesefeldt4, Gunter Folger4, Franca Foppiano, Alessandra Forti2, S. Garelli, S. Gianì4, R. Giannitrapani17, D. Gibin4, J. J. Gomez Y Cadenas4, I. González4, G. Gracia Abril4, G. Greeniaus18, Walter Greiner15, Vladimir Grichine, A. Grossheim4, Susanna Guatelli, P. Gumplinger11, R. Hamatsu19, K. Hashimoto, H. Hasui, A. Heikkinen20, A. S. Howard5, Vladimir Ivanchenko4, A. Johnson6, F.W. Jones11, J. Kallenbach, Naoko Kanaya4, M. Kawabata, Y. Kawabata, M. Kawaguti, S.R. Kelner21, Paul R. C. Kent22, A. Kimura23, T. Kodama24, R. P. Kokoulin21, M. Kossov13, Hisaya Kurashige25, E. Lamanna26, Tapio Lampén20, V. Lara4, Veronique Lefebure4, F. Lei16, M. Liendl4, W. S. Lockman, Francesco Longo27, S. Magni, M. Maire, E. Medernach4, K. Minamimoto24, P. Mora de Freitas, Yoshiyuki Morita3, K. Murakami3, M. Nagamatu24, R. Nartallo28, Petteri Nieminen28, T. Nishimura, K. Ohtsubo, M. Okamura, S. W. O'Neale29, Y. Oohata19, K. Paech15, J Perl6, Andreas Pfeiffer4, Maria Grazia Pia, F. Ranjard4, A.M. Rybin, S.S Sadilov4, E. Di Salvo8, Giovanni Santin27, Takashi Sasaki3, N. Savvas2, Y. Sawada, Stefan Scherer15, S. Sei24, V. Sirotenko4, David J. Smith6, N. Starkov, H. Stoecker15, J. Sulkimo20, M. Takahata23, Satoshi Tanaka30, E. Tcherniaev4, E. Safai Tehrani6, M. Tropeano1, P. Truscott31, H. Uno24, L. Urbán, P. Urban32, M. Verderi, A. Walkden2, W. Wander33, H. Weber15, J.P. Wellisch4, Torre Wenaus34, D.C. Williams, Douglas Wright6, T. Yamada24, H. Yoshida24, D. Zschiesche15 
Abstract: G eant 4 is a toolkit for simulating the passage of particles through matter. It includes a complete range of functionality including tracking, geometry, physics models and hits. The physics processes offered cover a comprehensive range, including electromagnetic, hadronic and optical processes, a large set of long-lived particles, materials and elements, over a wide energy range starting, in some cases, from 250 eV and extending in others to the TeV energy range. It has been designed and constructed to expose the physics models utilised, to handle complex geometries, and to enable its easy adaptation for optimal use in different sets of applications. The toolkit is the result of a worldwide collaboration of physicists and software engineers. It has been created exploiting software engineering and object-oriented technology and implemented in the C++ programming language. It has been used in applications in particle physics, nuclear physics, accelerator design, space engineering and medical physics.

16,046 citations


14


Journal ArticleDOI
TL;DR: A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression, finding in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function.
Abstract: A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is de- scribed that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression. The output is displayed graphically, conveying the clustering and the underlying expression data simultaneously in a form intuitive for biologists. We have found in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function, and we find a similar tendency in human data. Thus patterns seen in genome-wide expression experiments can be inter- preted as indications of the status of cellular processes. Also, coexpression of genes of known function with poorly charac- terized or novel genes may provide a simple means of gaining leads to the functions of many genes for which information is not available currently.

16,000 citations


Journal ArticleDOI
19 Apr 2000-JAMA
TL;DR: A checklist contains specifications for reporting of meta-analyses of observational studies in epidemiology, including background, search strategy, methods, results, discussion, and conclusion should improve the usefulness ofMeta-an analyses for authors, reviewers, editors, readers, and decision makers.
Abstract: ObjectiveBecause of the pressure for timely, informed decisions in public health and clinical practice and the explosion of information in the scientific literature, research results must be synthesized. Meta-analyses are increasingly used to address this problem, and they often evaluate observational studies. A workshop was held in Atlanta, Ga, in April 1997, to examine the reporting of meta-analyses of observational studies and to make recommendations to aid authors, reviewers, editors, and readers.ParticipantsTwenty-seven participants were selected by a steering committee, based on expertise in clinical practice, trials, statistics, epidemiology, social sciences, and biomedical editing. Deliberations of the workshop were open to other interested scientists. Funding for this activity was provided by the Centers for Disease Control and Prevention.EvidenceWe conducted a systematic review of the published literature on the conduct and reporting of meta-analyses in observational studies using MEDLINE, Educational Research Information Center (ERIC), PsycLIT, and the Current Index to Statistics. We also examined reference lists of the 32 studies retrieved and contacted experts in the field. Participants were assigned to small-group discussions on the subjects of bias, searching and abstracting, heterogeneity, study categorization, and statistical methods.Consensus ProcessFrom the material presented at the workshop, the authors developed a checklist summarizing recommendations for reporting meta-analyses of observational studies. The checklist and supporting evidence were circulated to all conference attendees and additional experts. All suggestions for revisions were addressed.ConclusionsThe proposed checklist contains specifications for reporting of meta-analyses of observational studies in epidemiology, including background, search strategy, methods, results, discussion, and conclusion. Use of the checklist should improve the usefulness of meta-analyses for authors, reviewers, editors, readers, and decision makers. An evaluation plan is suggested and research areas are explored.

15,106 citations


Authors

Showing all 125751 results

NameH-indexPapersCitations
Eric S. Lander301826525976
George M. Whitesides2401739269833
Yi Cui2201015199725
Yi Chen2174342293080
David Miller2032573204840
David Baltimore203876162955
Edward Witten202602204199
Irving L. Weissman2011141172504
Hongjie Dai197570182579
Robert M. Califf1961561167961
Frank E. Speizer193636135891
Thomas C. Südhof191653118007
Gad Getz189520247560
Mark Hallett1861170123741
John P. A. Ioannidis1851311193612
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2022177
202117,830
202018,226
201916,189
201814,684
201714,653

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Institution's top 5 most impactful journals

Social Science Research Network

6.8K papers, 333.2K citations

bioRxiv

3.6K papers, 19.5K citations

Science

2.5K papers, 719.5K citations

Nature

2.2K papers, 787.1K citations