Hunter B Fraser

Summary

Affiliation: University of California
Country: USA

Publications

  1. ncbi request reprint Evolutionary rate in the protein interaction network
    Hunter B Fraser
    Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
    Science 296:750-2. 2002
  2. pmc A simple dependence between protein evolution rate and the number of protein-protein interactions
    Hunter B Fraser
    Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
    BMC Evol Biol 3:11. 2003
  3. ncbi request reprint Modularity and evolutionary constraint on proteins
    Hunter B Fraser
    Department of Molecular and Cell Biology, University of California, Berkeley, California 94720, USA
    Nat Genet 37:351-2. 2005
  4. pmc Noise minimization in eukaryotic gene expression
    Hunter B Fraser
    Department of Molecular and Cell Biology, University of California, Berkeley, USA
    PLoS Biol 2:e137. 2004
  5. pmc Evolutionary rate depends on number of protein-protein interactions independently of gene expression level
    Hunter B Fraser
    Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
    BMC Evol Biol 4:13. 2004
  6. pmc Coevolution of gene expression among interacting proteins
    Hunter B Fraser
    Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
    Proc Natl Acad Sci U S A 101:9033-8. 2004
  7. pmc Conservation and evolution of cis-regulatory systems in ascomycete fungi
    Audrey P Gasch
    Genome Sciences Department, Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA
    PLoS Biol 2:e398. 2004
  8. pmc Aging and gene expression in the primate brain
    Hunter B Fraser
    Department of Molecular and Cell Biology, University of California, Berkeley, California, USA
    PLoS Biol 3:e274. 2005
  9. pmc Confirmation of organized modularity in the yeast interactome
    Nicolas Bertin
    PLoS Biol 5:e153. 2007
  10. ncbi request reprint Codon usage and selection on proteins
    Joshua B Plotkin
    Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA
    J Mol Evol 63:635-53. 2006

Detail Information

Publications18

  1. ncbi request reprint Evolutionary rate in the protein interaction network
    Hunter B Fraser
    Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
    Science 296:750-2. 2002
    ..We confirm one predicted outcome of this process-namely, that interacting proteins evolve at similar rates...
  2. pmc A simple dependence between protein evolution rate and the number of protein-protein interactions
    Hunter B Fraser
    Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
    BMC Evol Biol 3:11. 2003
    ..However, the generality of this observation has recently been challenged. Here we examine the problem using protein-protein interaction data from the yeast Saccharomyces cerevisiae and genome sequences from two other yeast species...
  3. ncbi request reprint Modularity and evolutionary constraint on proteins
    Hunter B Fraser
    Department of Molecular and Cell Biology, University of California, Berkeley, California 94720, USA
    Nat Genet 37:351-2. 2005
    ....
  4. pmc Noise minimization in eukaryotic gene expression
    Hunter B Fraser
    Department of Molecular and Cell Biology, University of California, Berkeley, USA
    PLoS Biol 2:e137. 2004
    ..Our results support the hypothesis that noise in gene expression is a biologically important variable, is generally detrimental to organismal fitness, and is subject to natural selection...
  5. pmc Evolutionary rate depends on number of protein-protein interactions independently of gene expression level
    Hunter B Fraser
    Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
    BMC Evol Biol 4:13. 2004
    ..A recent analysis suggested that the observed correlation between number of interactions and evolutionary rate may be due to experimental biases in high-throughput protein interaction data sets...
  6. pmc Coevolution of gene expression among interacting proteins
    Hunter B Fraser
    Department of Molecular and Cell Biology, University of California, Berkeley, CA 94720, USA
    Proc Natl Acad Sci U S A 101:9033-8. 2004
    ..Our results also suggest that expression coevolution can be used for computational prediction of protein-protein interactions...
  7. pmc Conservation and evolution of cis-regulatory systems in ascomycete fungi
    Audrey P Gasch
    Genome Sciences Department, Genomics Division, Lawrence Berkeley National Laboratory, Berkeley, California, USA
    PLoS Biol 2:e398. 2004
    ..Our results suggest that the DNA binding specificity of these proteins has coevolved with the sequences found upstream of the Rpn4p target genes and suggest that Rpn4p has a different function in N. crassa...
  8. pmc Aging and gene expression in the primate brain
    Hunter B Fraser
    Department of Molecular and Cell Biology, University of California, Berkeley, California, USA
    PLoS Biol 3:e274. 2005
    ....
  9. pmc Confirmation of organized modularity in the yeast interactome
    Nicolas Bertin
    PLoS Biol 5:e153. 2007
  10. ncbi request reprint Codon usage and selection on proteins
    Joshua B Plotkin
    Department of Biology, University of Pennsylvania, Philadelphia, PA 19104, USA
    J Mol Evol 63:635-53. 2006
    ..We also discuss several confounding factors, neglected by the Fisher-Wright model, that may limit the applicability of volatility in practice...
  11. ncbi request reprint Coevolution, modularity and human disease
    Hunter B Fraser
    Broad Institute of Harvard and Massachusetts Institute of Technology, Cambridge, MA 02142, USA
    Curr Opin Genet Dev 16:637-44. 2006
    ..Moreover, the combination of these two ideas might have implications for our understanding of many aspects of biology, ranging from the general architecture of living systems to the causes of various human diseases...
  12. ncbi request reprint Assessing the determinants of evolutionary rates in the presence of noise
    Joshua B Plotkin
    Department of Biology, The University of Pennsylvania, USA
    Mol Biol Evol 24:1113-21. 2007
    ..More accurate measurements or more sophisticated statistical techniques will be required to determine which one, if any, of these factors dominates protein evolution...
  13. ncbi request reprint Estimating selection pressures from limited comparative data
    Joshua B Plotkin
    Mol Biol Evol 23:1457-9. 2006
    ..The regression technique does not depend on an underlying population-genetic mechanism. This new approach to estimating selection across a genome should be more powerful and more widely applicable than volatility itself...
  14. pmc Sum1p, the origin recognition complex, and the spreading of a promoter-specific repressor in Saccharomyces cerevisiae
    Patrick J Lynch
    Department of Biochemistry and Institute for Genome Sciences and Policy, Duke University, 101 Science Drive, Box 3382, Durham, North Carolina 27708, USA
    Mol Cell Biol 25:5920-32. 2005
    ..Finally, this study uncovered a functional connection between wild-type Sum1p and the origin recognition complex, and this relationship also contributes to mutant Sum1-1p localization...
  15. pmc Functional genomic analysis of the rates of protein evolution
    Dennis P Wall
    Department of Biological Sciences, and Stanford Genome Technology Center, Stanford University, Stanford, CA 94305, USA
    Proc Natl Acad Sci U S A 102:5483-8. 2005
    ....
  16. ncbi request reprint Adjusting for selection on synonymous sites in estimates of evolutionary distance
    Aaron E Hirsh
    Department of Biological Sciences, Stanford University, Stanford, California, USA
    Mol Biol Evol 22:174-7. 2005
    ..Here, we use the relationship between codon bias and synonymous divergence observed in four species of the genus Saccharomyces to provide a simple correction for selection on silent sites...
  17. ncbi request reprint Detecting selection using a single genome sequence of M. tuberculosis and P. falciparum
    Joshua B Plotkin
    Harvard Society of Fellows and Bauer Center for Genomics Research, 7 Divinity Avenue, Cambridge, Massachusetts 02138, USA
    Nature 428:942-5. 2004
    ..Our method of estimating selective pressures requires far fewer data than comparative sequence analysis, and it measures selection across an entire genome; the method can readily be applied to a large range of sequenced organisms...
  18. pmc Using protein complexes to predict phenotypic effects of gene mutation
    Hunter B Fraser
    Broad Institute of Harvard and MIT, 320 Charles St, Cambridge, Massachhusetts 02142, USA
    Genome Biol 8:R252. 2007
    ..Predicting the phenotypic effects of mutations is a central goal of genetics research; it has important applications in elucidating how genotype determines phenotype and in identifying human disease genes...