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Institution

University of California, San Francisco

EducationSan Francisco, California, United States
About: University of California, San Francisco is a education organization based out in San Francisco, California, United States. It is known for research contribution in the topics: Population & Health care. The organization has 83381 authors who have published 186236 publications receiving 12068420 citations. The organization is also known as: UCSF & UC San Francisco.


Papers
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Journal ArticleDOI
TL;DR: In this article, the authors reviewed recent data on the clinical course, therapeutic options, and underlying mechanisms thought to be involved in the pathogenesis of idiopathic pulmonary fibrosis.

1,614 citations

Journal ArticleDOI
TL;DR: A novel protein-ligand docking method that accurately accounts for both ligand and receptor flexibility by iteratively combining rigid receptor docking (Glide) with protein structure prediction (Prime) techniques is presented.
Abstract: We present a novel protein-ligand docking method that accurately accounts for both ligand and receptor flexibility by iteratively combining rigid receptor docking (Glide) with protein structure prediction (Prime) techniques. While traditional rigid-receptor docking methods are useful when the receptor structure does not change substantially upon ligand binding, success is limited when the protein must be "induced" into the correct binding conformation for a given ligand. We provide an in-depth description of our novel methodology and present results for 21 pharmaceutically relevant examples. Traditional rigid-receptor docking for these 21 cases yields an average RMSD of 5.5 A. The average ligand RMSD for docking to a flexible receptor for the 21 pairs is 1.4 A; the RMSD is < or =1.8 A for 18 of the cases. For the three cases with RMSDs greater than 1.8 A, the core of the ligand is properly docked and all key protein/ligand interactions are captured.

1,612 citations

Journal ArticleDOI
TL;DR: A predictive method for designing synthetic ribosome binding sites is developed, enabling a rational control over the protein expression level, and is demonstrated by rationally optimizing protein expression to connect a genetic sensor to a synthetic circuit.
Abstract: Microbial engineering often requires fine control over protein expression--for example, to connect genetic circuits or control flux through a metabolic pathway. To circumvent the need for trial and error optimization, we developed a predictive method for designing synthetic ribosome binding sites, enabling a rational control over the protein expression level. Experimental validation of >100 predictions in Escherichia coli showed that the method is accurate to within a factor of 2.3 over a range of 100,000-fold. The design method also correctly predicted that reusing identical ribosome binding site sequences in different genetic contexts can result in different protein expression levels. We demonstrate the method's utility by rationally optimizing protein expression to connect a genetic sensor to a synthetic circuit. The proposed forward engineering approach should accelerate the construction and systematic optimization of large genetic systems.

1,611 citations

Journal ArticleDOI
08 Jul 2010-Nature
TL;DR: An in-depth investigation of the human SHANK3 locus and its mouse homologue demonstrated that this tissue-specific DNA methylation regulates intragenic promoter activity in vitro and in vivo.
Abstract: Although it is known that the methylation of DNA in 5' promoters suppresses gene expression, the role of DNA methylation in gene bodies is unclear. In mammals, tissue- and cell type-specific methylation is present in a small percentage of 5' CpG island (CGI) promoters, whereas a far greater proportion occurs across gene bodies, coinciding with highly conserved sequences. Tissue-specific intragenic methylation might reduce, or, paradoxically, enhance transcription elongation efficiency. Capped analysis of gene expression (CAGE) experiments also indicate that transcription commonly initiates within and between genes. To investigate the role of intragenic methylation, we generated a map of DNA methylation from the human brain encompassing 24.7 million of the 28 million CpG sites. From the dense, high-resolution coverage of CpG islands, the majority of methylated CpG islands were shown to be in intragenic and intergenic regions, whereas less than 3% of CpG islands in 5' promoters were methylated. The CpG islands in all three locations overlapped with RNA markers of transcription initiation, and unmethylated CpG islands also overlapped significantly with trimethylation of H3K4, a histone modification enriched at promoters. The general and CpG-island-specific patterns of methylation are conserved in mouse tissues. An in-depth investigation of the human SHANK3 locus and its mouse homologue demonstrated that this tissue-specific DNA methylation regulates intragenic promoter activity in vitro and in vivo. These methylation-regulated, alternative transcripts are expressed in a tissue- and cell type-specific manner, and are expressed differentially within a single cell type from distinct brain regions. These results support a major role for intragenic methylation in regulating cell context-specific alternative promoters in gene bodies.

1,610 citations

Journal ArticleDOI
TL;DR: Patterns of the epidemiological transition with a composite indicator of sociodemographic status, which was constructed from income per person, average years of schooling after age 15 years, and the total fertility rate and mean age of the population, were quantified.

1,609 citations


Authors

Showing all 84066 results

NameH-indexPapersCitations
Robert Langer2812324326306
Meir J. Stampfer2771414283776
Gordon H. Guyatt2311620228631
Eugene Braunwald2301711264576
John Q. Trojanowski2261467213948
Fred H. Gage216967185732
Robert J. Lefkowitz214860147995
Peter Libby211932182724
Edward Giovannucci2061671179875
Rob Knight2011061253207
Irving L. Weissman2011141172504
Eugene V. Koonin1991063175111
Peter J. Barnes1941530166618
Virginia M.-Y. Lee194993148820
Gordon B. Mills1871273186451
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Performance
Metrics
No. of papers from the Institution in previous years
YearPapers
20241
2023179
2022981
202111,518
202010,575
20199,343