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Institution

University of Amsterdam

EducationAmsterdam, Noord-Holland, Netherlands
About: University of Amsterdam is a education organization based out in Amsterdam, Noord-Holland, Netherlands. It is known for research contribution in the topics: Population & Context (language use). The organization has 59309 authors who have published 140894 publications receiving 5984137 citations. The organization is also known as: UvA & Universiteit van Amsterdam.


Papers
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Journal ArticleDOI
TL;DR: An analysis of response latencies shows that when an image is presented to the visual system, neuronal activity is rapidly routed to a large number of visual areas, but the activity of cortical neurons is not determined by this feedforward sweep alone.

2,148 citations

Journal ArticleDOI
TL;DR: The results show that MAGMA has significantly more power than other tools for both the gene and the gene-set analysis, identifying more genes and gene sets associated with Crohn’s Disease while maintaining a correct type 1 error rate.
Abstract: By aggregating data for complex traits in a biologically meaningful way, gene and gene-set analysis constitute a valuable addition to single-marker analysis. However, although various methods for gene and gene-set analysis currently exist, they generally suffer from a number of issues. Statistical power for most methods is strongly affected by linkage disequilibrium between markers, multi-marker associations are often hard to detect, and the reliance on permutation to compute p-values tends to make the analysis computationally very expensive. To address these issues we have developed MAGMA, a novel tool for gene and gene-set analysis. The gene analysis is based on a multiple regression model, to provide better statistical performance. The gene-set analysis is built as a separate layer around the gene analysis for additional flexibility. This gene-set analysis also uses a regression structure to allow generalization to analysis of continuous properties of genes and simultaneous analysis of multiple gene sets and other gene properties. Simulations and an analysis of Crohn’s Disease data are used to evaluate the performance of MAGMA and to compare it to a number of other gene and gene-set analysis tools. The results show that MAGMA has significantly more power than other tools for both the gene and the gene-set analysis, identifying more genes and gene sets associated with Crohn’s Disease while maintaining a correct type 1 error rate. Moreover, the MAGMA analysis of the Crohn’s Disease data was found to be considerably faster as well.

2,147 citations

Journal ArticleDOI
TL;DR: In this paper, the authors proposed a rank test based on matrix perturbation theory, which overcomes deficiencies of existing rank statistics, such as: a Kronecker covariance matrix for the canonical correlation rank statistic of Anderson [Annals of Mathematical Statistics (1951), 22, 327-351] sensitivity to the ordering of the variables for the LDU rank statistics of Cragg and Donald [1996, 91, 1301-1309] and Gill and Lewbel [Journal of the American Statistical Association (1992), 87, 766-776] a limiting

2,125 citations

Journal ArticleDOI
28 Oct 2015-BMJ
TL;DR: STARD 2015 is presented, an updated list of 30 essential items that should be included in every report of a diagnostic accuracy study, which incorporates recent evidence about sources of bias and variability in diagnostic accuracy.
Abstract: Incomplete reporting has been identified as a major source of avoidable waste in biomedical research. Essential information is often not provided in study reports, impeding the identification, critical appraisal, and replication of studies. To improve the quality of reporting of diagnostic accuracy studies, the Standards for Reporting Diagnostic Accuracy (STARD) statement was developed. Here we present STARD 2015, an updated list of 30 essential items that should be included in every report of a diagnostic accuracy study. This update incorporates recent evidence about sources of bias and variability in diagnostic accuracy and is intended to facilitate the use of STARD. As such, STARD 2015 may help to improve completeness and transparency in reporting of diagnostic accuracy studies.

2,116 citations

Journal ArticleDOI
04 Aug 2005-Nature
TL;DR: It is shown that sustained BRAFV600E expression in human melanocytes induces cell cycle arrest, which is accompanied by the induction of both p16INK4a and senescence-associated acidic β-galactosidase (SA-β-Gal) activity, a commonly usedsenescence marker.
Abstract: Cellular senescence, a growth-arrest program that limits the lifespan of mammalian cells and prevents unlimited cell proliferation, is attracting considerable interest because of its links to tumour suppression. Using a mouse model in which the oncogene Ras is activated in the haematopoietic compartment of bone marrow, Braig et al. show that cellular senescence can block lymphoma development. Genetic inactivation of the histone methyltransferase Suv39h1 that controls senescence by ‘epigenetic’ modification of DNA-associated proteins, or a pharmacological approach that mimics loss of this enzyme, allow the formation of malignant lymphomas in response to oncogenic Ras. This work has important implications for both tumour development and tumour therapy. Michaloglou et al. report that oncogene-induced senescence may be a physiologically important process in humans, keeping moles in a benign state for many years: unchecked they develop into malignant melanomas. Chen et al. also find that cellular senescence blocks tumorigenesis in vivo: they show that acting together, the p53 tumour suppressor and the cellular senescence system can prevent prostate cancer induction in mice by the PTEN mutation. Collado et al. show that cellular senescence is a defining feature of Ras-initiated premalignant tumours; this could prove valuable in the diagnosis and prognosis of cancer. See the web focus . Most normal mammalian cells have a finite lifespan1, thought to constitute a protective mechanism against unlimited proliferation2,3,4. This phenomenon, called senescence, is driven by telomere attrition, which triggers the induction of tumour suppressors including p16INK4a (ref. 5). In cultured cells, senescence can be elicited prematurely by oncogenes6; however, whether such oncogene-induced senescence represents a physiological process has long been debated. Human naevi (moles) are benign tumours of melanocytes that frequently harbour oncogenic mutations (predominantly V600E, where valine is substituted for glutamic acid) in BRAF7, a protein kinase and downstream effector of Ras. Nonetheless, naevi typically remain in a growth-arrested state for decades and only rarely progress into malignancy (melanoma)8,9,10. This raises the question of whether naevi undergo BRAFV600E-induced senescence. Here we show that sustained BRAFV600E expression in human melanocytes induces cell cycle arrest, which is accompanied by the induction of both p16INK4a and senescence-associated acidic β-galactosidase (SA-β-Gal) activity, a commonly used senescence marker. Validating these results in vivo, congenital naevi are invariably positive for SA-β-Gal, demonstrating the presence of this classical senescence-associated marker in a largely growth-arrested, neoplastic human lesion. In growth-arrested melanocytes, both in vitro and in situ, we observed a marked mosaic induction of p16INK4a, suggesting that factors other than p16INK4a contribute to protection against BRAFV600E-driven proliferation. Naevi do not appear to suffer from telomere attrition, arguing in favour of an active oncogene-driven senescence process, rather than a loss of replicative potential. Thus, both in vitro and in vivo, BRAFV600E-expressing melanocytes display classical hallmarks of senescence, suggesting that oncogene-induced senescence represents a genuine protective physiological process.

2,074 citations


Authors

Showing all 59759 results

NameH-indexPapersCitations
Richard A. Flavell2311328205119
Scott M. Grundy187841231821
Stuart H. Orkin186715112182
Kenneth C. Anderson1781138126072
David A. Weitz1781038114182
Dorret I. Boomsma1761507136353
Brenda W.J.H. Penninx1701139119082
Michael Kramer1671713127224
Nicholas J. White1611352104539
Lex M. Bouter158767103034
Wolfgang Wagner1562342123391
Jerome I. Rotter1561071116296
David Cella1561258106402
David Eisenberg156697112460
Naveed Sattar1551326116368
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
2023198
2022699
20219,646
20208,532
20197,821
20186,407