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  1. Molecular Genetics of Natural Populations | Molecular Biology and Evolution | Oxford Academic
  2. Scientists develop new theory of molecular evolution
  3. Background
  4. Integrated Molecular Evolution
  5. Background

Wilke is the author of approximately scientific papers. In , Dr.

Molecular Genetics of Natural Populations | Molecular Biology and Evolution | Oxford Academic

Abstract Much molecular-evolution research is concerned with sequence analysis. Introduction The field of molecular evolution investigates how genes and genomes evolve over time. Identifying Fundamental Principles of Molecular Evolution Besides understanding and interpreting specific evolutionary events, evolutionary biologists also aim to identify fundamental principles of molecular evolution. Predicting Probable Evolutionary Trajectories For many real-world applications, it would be useful to be able to predict future evolutionary events.

Summary There is a growing trend in widely differing subfields of molecular evolution to increase biophysical realism in computational models of sequence evolution. Author's Biography Claus O. References 1. View Article Google Scholar 2. View Article Google Scholar 3. Mol Biol Evol — View Article Google Scholar 4.

Gene — View Article Google Scholar 5. Rodrigue N, Kleinman CL, Philippe H, Lartillot N Computational methods for evaluating phylogenetic models of coding sequence evolution with dependence between codons. View Article Google Scholar 6. Rodrigue N, Philippe H Mechanistic revisions of phenomenological modeling strategies in molecular evolution. Trends Genet — View Article Google Scholar 7.

Gene 45— View Article Google Scholar 8. Syst Biol 60— View Article Google Scholar 9. BMC Evol Biol View Article Google Scholar Gouy M, Gautier C Codon usage in bacteria: correlation with gene expressivity. Nucleic Acids Res — J Mol Evol — Genetics — Drummond DA, Wilke CO Mistranslation-induced protein misfolding as a dominant constraint on coding-sequence evolution.

Scientists develop new theory of molecular evolution

Cell — Mol Syst Biol 6: Cherry JL Expression level, evolutionary rate, and the cost of expression. Genome Biol Evol 2: — PLoS Comput Biol 2: e PLoS Comput Biol 6: e Heo M, Shakhnovich EI Interplay between pleiotropy and secondary selection determines rise and fall of mutators in stress response. Biophys J — Zhang J, Maslov S, Shakhnovich EI Constraints imposed by non-functional protein-protein interactions on gene expression and proteome size.

Mol Syst Biol 4: Wagner A Neutralism and selectionism: a network-based reconciliation.

Nat Rev Genet 9: — Ferrada E, Wagner A Protein robustness promotes evolutionary innovations on large evolutionary time-scales. Proc R Soc B — Rajon E, Masel J Evolution of molecular error rates and the consequences for evolvability. Avian Dis — J Virol — Nature Rev Microbiol 5: — Bioinformatics 34— Heredity — Nat Rev Genet — Nature — Montero, C.

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Sanz, M. Eigen and P. Schuster: The hypercycle: a principle of natural self-organization, Springer-Verlag, Berlin, Boerlijst and P. Biosphere, Vol.


Cronhjort and C. Scheuring, T. Lee, K. Severin, Y. Yokobayashi, M. Sievert and G. Scheruing, and E. Scheuring et al.

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Previous Article. Gene expression profiling using whole genome microarray with 4, open reading frames revealed over-representation of the transport functional category in all evolved lines. Excess nutrient adapted lines were found to exhibit greater degrees of positive correlation, indicating parallelism between ancestor and evolved lines, when compared with prolonged stationary phase adapted lines. Gene-metabolite correlation network analysis revealed over-representation of membrane-associated functional categories. Proteome analysis revealed the major role played by outer membrane proteins in adaptive evolution.

Molecular Evolution: Genes And Proteins

In summary, we report the vital involvement of energy metabolism and membrane-associated functional categories in all of the evolutionary conditions examined in this study within the context of transcript, outer membrane protein, and metabolite levels. These initial data obtained may help to enhance our understanding of the evolutionary process from a systems biology perspective. Most micro-organisms grow in environments that are not favorable for their growth.

The level of nutrients available to them is rarely optimal.