Christoph Adami

Prof. Christoph Adami

Microbiology and Molecular Genetics & Physics and Astronomy, Michigan State University, MI 48824, USA
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Research Focus & Metrics

Academic Career Length

39Years (1988-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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21 September 2005 in Proceedings of the National Academy of Sciences
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Journal Article
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DDD. Allan Drummond
D. Allan Drummond
JBJesse Bloom
Jesse Bloom
Christoph AdamiChristoph Adami
Christoph Adami
CWClaus Wilke
Claus Wilke
FAFrances H. Arnold
Frances H. Arnold
Much recent work has explored molecular and population-genetic constraints on the rate of protein sequence evolution. The best predictor of evolutionary rate is expression level, for reasons that have remained unexplained. Here, we hypothesize that selection to reduce the burden of protein misfolding will favor protein sequences with increased robustness to translational missense errors. Pressure for translational robustness increases with expression level and constrains sequence evolution. Using several sequenced yeast genomes, global expression and protein abundance data, and sets of paralogs traceable to an ancient whole-genome duplication in yeast, we rule out several confounding effects and show that expression level explains roughly half the variation inSaccharomyces cerevisiaeprotein evolutionary rates. We examine causes for expression's dominant role and find that genome-wide tests favor the translational robustness explanation over existing hypotheses that invoke constraints on function or translational efficiency. Our results suggest that proteins evolve at rates largely unrelated to their functions and can explain why highly expressed proteins evolve slowly across the tree of life.

1 May 2003 in Nature
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Journal Article
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RLRichard E. Lenski
Richard E. Lenski
COCharles Ofria
Charles Ofria
RPRobert T. Pennock
Robert T. Pennock
Christoph AdamiChristoph Adami
Christoph Adami

19 July 2001 in Nature
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Journal Article
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CWClaus Wilke
Claus Wilke
JWJia Lan Wang
Jia Lan Wang
COCharles Ofria
Charles Ofria
RLRichard E. Lenski
Richard E. Lenski
Christoph AdamiChristoph Adami
Christoph Adami

29 December 1997 in Physical Review Letters
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NCN. J. Cerf
N. J. Cerf
Christoph AdamiChristoph Adami
Christoph Adami
A framework for a quantum mechanical information theory is introduced that is based entirely on density operators, and gives rise to a unified description of classical correlation and quantum entanglement. Unlike in classical (Shannon) information theory, quantum (von Neumann) conditional entropies can be negative when considering quantum entangled systems, a fact related to quantum nonseparability. The possibility that negative (virtual) information can be carried by entangled particles suggests a consistent interpretation of quantum informational processes.

25 April 2000 in Proceedings of the National Academy of Sciences
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Christoph AdamiChristoph Adami
Christoph Adami
COCharles Ofria
Charles Ofria
TCTravis C. Collier
Travis C. Collier
To make a case for or against a trend in the evolution of complexity in biological evolution, complexity needs to be both rigorously defined and measurable. A recent information-theoretic (but intuitively evident) definition identifies genomic complexity with the amount of information a sequence stores about its environment. We investigate the evolution of genomic complexity in populations of digital organisms and monitor in detail the evolutionary transitions that increase complexity. We show that, because natural selection forces genomes to behave as a natural “Maxwell Demon,” within a fixed environment, genomic complexity is forced to increase.

11 January 2005 in Proceedings of the National Academy of Sciences
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Journal Article
Closed access
JBJesse Bloom
Jesse Bloom
JSJonathan J. Silberg
Jonathan J. Silberg
CWClaus Wilke
Claus Wilke
DDD. Allan Drummond
D. Allan Drummond
Christoph AdamiChristoph Adami
Christoph Adami
FAFrances H. Arnold
Frances H. Arnold
We present a simple theory that uses thermodynamic parameters to predict the probability that a protein retains the wild-type structure after one or more random amino acid substitutions. Our theory predicts that for large numbers of substitutions the probability that a protein retains its structure will decline exponentially with the number of substitutions, with the severity of this decline determined by properties of the structure. Our theory also predicts that a protein can gain extra robustness to the first few substitutions by increasing its thermodynamic stability. We validate our theory with simulations on lattice protein models and by showing that it quantitatively predicts previously published experimental measurements on subtilisin and our own measurements on variants of TEM1 β-lactamase. Our work unifies observations about the clustering of functional proteins in sequence space, and provides a basis for interpreting the response of proteins to substitutions in protein engineering applications.