Institution
National Institutes of Health
Government•Bethesda, Maryland, United States•
About: National Institutes of Health is a government organization based out in Bethesda, Maryland, United States. It is known for research contribution in the topics: Population & Gene. The organization has 149298 authors who have published 297896 publications receiving 21337431 citations. The organization is also known as: NIH & U.S. National Institutes of Health.
Topics: Population, Gene, Cancer, Receptor, Immune system
Papers published on a yearly basis
Papers
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TL;DR: In the Global Burden of Disease Study 2013 (GBD 2013) as mentioned in this paper, the authors estimated the quantities for acute and chronic diseases and injuries for 188 countries between 1990 and 2013.
4,510 citations
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TL;DR: A new software tool called Primer-BLAST is presented to alleviate the difficulty in designing target-specific primers and combines BLAST with a global alignment algorithm to ensure a full primer-target alignment and is sensitive enough to detect targets that have a significant number of mismatches to primers.
Abstract: Choosing appropriate primers is probably the single most important factor affecting the polymerase chain reaction (PCR). Specific amplification of the intended target requires that primers do not have matches to other targets in certain orientations and within certain distances that allow undesired amplification. The process of designing specific primers typically involves two stages. First, the primers flanking regions of interest are generated either manually or using software tools; then they are searched against an appropriate nucleotide sequence database using tools such as BLAST to examine the potential targets. However, the latter is not an easy process as one needs to examine many details between primers and targets, such as the number and the positions of matched bases, the primer orientations and distance between forward and reverse primers. The complexity of such analysis usually makes this a time-consuming and very difficult task for users, especially when the primers have a large number of hits. Furthermore, although the BLAST program has been widely used for primer target detection, it is in fact not an ideal tool for this purpose as BLAST is a local alignment algorithm and does not necessarily return complete match information over the entire primer range. We present a new software tool called Primer-BLAST to alleviate the difficulty in designing target-specific primers. This tool combines BLAST with a global alignment algorithm to ensure a full primer-target alignment and is sensitive enough to detect targets that have a significant number of mismatches to primers. Primer-BLAST allows users to design new target-specific primers in one step as well as to check the specificity of pre-existing primers. Primer-BLAST also supports placing primers based on exon/intron locations and excluding single nucleotide polymorphism (SNP) sites in primers. We describe a robust and fully implemented general purpose primer design tool that designs target-specific PCR primers. Primer-BLAST offers flexible options to adjust the specificity threshold and other primer properties. This tool is publicly available at http://www.ncbi.nlm.nih.gov/tools/primer-blast
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4,433 citations
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TL;DR: A model for the organization of this system that emphasizes a distinction between the representation of invariant and changeable aspects of faces is proposed and is hierarchical insofar as it is divided into a core system and an extended system.
4,430 citations
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TL;DR: A fundamental problem with cancer genome studies is described: as the sample size increases, the list of putatively significant genes produced by current analytical methods burgeons into the hundreds and the list includes many implausible genes, suggesting extensive false-positive findings that overshadow true driver events.
Abstract: Major international projects are underway that are aimed at creating a comprehensive catalogue of all the genes responsible for the initiation and progression of cancer. These studies involve the sequencing of matched tumour-normal samples followed by mathematical analysis to identify those genes in which mutations occur more frequently than expected by random chance. Here we describe a fundamental problem with cancer genome studies: as the sample size increases, the list of putatively significant genes produced by current analytical methods burgeons into the hundreds. The list includes many implausible genes (such as those encoding olfactory receptors and the muscle protein titin), suggesting extensive false-positive findings that overshadow true driver events. We show that this problem stems largely from mutational heterogeneity and provide a novel analytical methodology, MutSigCV, for resolving the problem. We apply MutSigCV to exome sequences from 3,083 tumour-normal pairs and discover extraordinary variation in mutation frequency and spectrum within cancer types, which sheds light on mutational processes and disease aetiology, and in mutation frequency across the genome, which is strongly correlated with DNA replication timing and also with transcriptional activity. By incorporating mutational heterogeneity into the analyses, MutSigCV is able to eliminate most of the apparent artefactual findings and enable the identification of genes truly associated with cancer.
4,411 citations
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TL;DR: The DBP results suggest that for the large majority of individuals, whether conventionally "hypertensive" or "normotensive", a lower blood pressure should eventually confer a lower risk of vascular disease.
4,397 citations
Authors
Showing all 149386 results
Name | H-index | Papers | Citations |
---|---|---|---|
Walter C. Willett | 334 | 2399 | 413322 |
Eric S. Lander | 301 | 826 | 525976 |
Robert Langer | 281 | 2324 | 326306 |
Meir J. Stampfer | 277 | 1414 | 283776 |
JoAnn E. Manson | 270 | 1819 | 258509 |
Albert Hofman | 267 | 2530 | 321405 |
Frank B. Hu | 250 | 1675 | 253464 |
Paul M. Ridker | 233 | 1242 | 245097 |
Solomon H. Snyder | 232 | 1222 | 200444 |
Salim Yusuf | 231 | 1439 | 252912 |
Eugene Braunwald | 230 | 1711 | 264576 |
Ralph B. D'Agostino | 226 | 1287 | 229636 |
John Q. Trojanowski | 226 | 1467 | 213948 |
Steven A. Rosenberg | 218 | 1204 | 199262 |
Yi Chen | 217 | 4342 | 293080 |