Institution
Fred Hutchinson Cancer Research Center
Nonprofit•Cape Town, South Africa•
About: Fred Hutchinson Cancer Research Center is a nonprofit organization based out in Cape Town, South Africa. It is known for research contribution in the topics: Population & Transplantation. The organization has 12322 authors who have published 30954 publications receiving 2288772 citations. The organization is also known as: Fred Hutch & The Hutch.
Topics: Population, Transplantation, Cancer, Breast cancer, Prostate cancer
Papers published on a yearly basis
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TL;DR: Hi-C is described, a method that probes the three-dimensional architecture of whole genomes by coupling proximity-based ligation with massively parallel sequencing and demonstrates the power of Hi-C to map the dynamic conformations of entire genomes.
Abstract: We describe Hi-C, a method that probes the three-dimensional architecture of whole genomes by coupling proximity-based ligation with massively parallel sequencing. We constructed spatial proximity maps of the human genome with Hi-C at a resolution of 1 megabase. These maps confirm the presence of chromosome territories and the spatial proximity of small, gene-rich chromosomes. We identified an additional level of genome organization that is characterized by the spatial segregation of open and closed chromatin to form two genome-wide compartments. At the megabase scale, the chromatin conformation is consistent with a fractal globule, a knot-free, polymer conformation that enables maximally dense packing while preserving the ability to easily fold and unfold any genomic locus. The fractal globule is distinct from the more commonly used globular equilibrium model. Our results demonstrate the power of Hi-C to map the dynamic conformations of whole genomes.
7,180 citations
TL;DR: This work has derived substitution matrices from about 2000 blocks of aligned sequence segments characterizing more than 500 groups of related proteins, leading to marked improvements in alignments and in searches using queries from each of the groups.
Abstract: Methods for alignment of protein sequences typically measure similarity by using a substitution matrix with scores for all possible exchanges of one amino acid with another. The most widely used matrices are based on the Dayhoff model of evolutionary rates. Using a different approach, we have derived substitution matrices from about 2000 blocks of aligned sequence segments characterizing more than 500 groups of related proteins. This led to marked improvements in alignments and in searches using queries from each of the groups.
6,553 citations
TL;DR: This protocol describes the use of the 'Sorting Tolerant From Intolerant' (SIFT) algorithm in predicting whether an AAS affects protein function.
Abstract: The effect of genetic mutation on phenotype is of significant interest in genetics. The type of genetic mutation that causes a single amino acid substitution (AAS) in a protein sequence is called a non-synonymous single nucleotide polymorphism (nsSNP). An nsSNP could potentially affect the function of the protein, subsequently altering the carrier's phenotype. This protocol describes the use of the 'Sorting Tolerant From Intolerant' (SIFT) algorithm in predicting whether an AAS affects protein function. To assess the effect of a substitution, SIFT assumes that important positions in a protein sequence have been conserved throughout evolution and therefore substitutions at these positions may affect protein function. Thus, by using sequence homology, SIFT predicts the effects of all possible substitutions at each position in the protein sequence. The protocol typically takes 5–20 min, depending on the input. SIFT is available as an online tool (
http://sift-dna.org
).
6,154 citations
Baylor College of Medicine1, Chinese Academy of Sciences2, Chinese National Human Genome Center3, University of Hong Kong4, The Chinese University of Hong Kong5, Hong Kong University of Science and Technology6, Illumina7, McGill University8, Washington University in St. Louis9, University of California, San Francisco10, Wellcome Trust Sanger Institute11, Beijing Normal University12, Health Sciences University of Hokkaido13, Shinshu University14, University of Tsukuba15, Howard University16, University of Ibadan17, Case Western Reserve University18, University of Utah19, Cold Spring Harbor Laboratory20, Johns Hopkins University21, University of Oxford22, North Carolina State University23, National Institutes of Health24, Massachusetts Institute of Technology25, Chinese Academy of Social Sciences26, Kyoto University27, Nagasaki University28, Wellcome Trust29, Genome Canada30, Foundation for the National Institutes of Health31, University of Maryland, Baltimore32, Vanderbilt University33, Stanford University34, New York University35, University of California, Berkeley36, University of Oklahoma37, University of New Mexico38, Université de Montréal39, University of California, Los Angeles40, University of Michigan41, University of Wisconsin-Madison42, London School of Economics and Political Science43, Genetic Alliance44, GlaxoSmithKline45, University of Washington46, Harvard University47, University of Chicago48, Fred Hutchinson Cancer Research Center49, University of Tokyo50
TL;DR: The HapMap will allow the discovery of sequence variants that affect common disease, will facilitate development of diagnostic tools, and will enhance the ability to choose targets for therapeutic intervention.
Abstract: The goal of the International HapMap Project is to determine the common patterns of DNA sequence variation in the human genome and to make this information freely available in the public domain. An international consortium is developing a map of these patterns across the genome by determining the genotypes of one million or more sequence variants, their frequencies and the degree of association between them, in DNA samples from populations with ancestry from parts of Africa, Asia and Europe. The HapMap will allow the discovery of sequence variants that affect common disease, will facilitate development of diagnostic tools, and will enhance our ability to choose targets for therapeutic intervention.
5,926 citations
University of North Carolina at Chapel Hill1, Fred Hutchinson Cancer Research Center2, FHI 3603, University of Zimbabwe4, Johns Hopkins University5, Oswaldo Cruz Foundation6, Chiang Mai University7, Fenway Health8, Harvard University9, Kenya Medical Research Institute10, University of the Witwatersrand11, University of California, San Francisco12, University of Nebraska Medical Center13, National Institutes of Health14, University of California, Los Angeles15, University of Washington16
TL;DR: In this article, Antiretroviral therapy that reduces viral replication could limit the transmission of human immunodeficiency virus type 1 (HIV-1) in serodiscordant couples.
Abstract: Background Antiretroviral therapy that reduces viral replication could limit the transmission of human immunodeficiency virus type 1 (HIV-1) in serodiscordant couples. Methods In nine countries, we...
5,871 citations
Authors
Showing all 12368 results
| Name | H-index | Papers | Citations |
|---|---|---|---|
| Walter C. Willett | 334 | 2399 | 413322 |
| Robert Langer | 281 | 2324 | 326306 |
| Meir J. Stampfer | 277 | 1414 | 283776 |
| JoAnn E. Manson | 270 | 1819 | 258509 |
| David J. Hunter | 213 | 1836 | 207050 |
| Peer Bork | 206 | 697 | 245427 |
| Eric Boerwinkle | 183 | 1321 | 170971 |
| Ruedi Aebersold | 182 | 879 | 141881 |
| Bruce M. Psaty | 181 | 1205 | 138244 |
| Aaron R. Folsom | 181 | 1118 | 134044 |
| David Baker | 173 | 1226 | 109377 |
| Frederick W. Alt | 171 | 577 | 95573 |
| Lily Yeh Jan | 162 | 467 | 73655 |
| Yuh Nung Jan | 162 | 460 | 74818 |
| Charles N. Serhan | 158 | 728 | 84810 |