The study of the evolution of metabolism is central to understanding the adaptive processes of cellular life, the emergence of high levels of organization (multicellularity), and the diversity and complexity of the living world [ 1, 2].
Whether adaptation is or is not contingent therefore has important implications for our understanding of the adaptive process and the predictability of evolution more generally.
While these results are in themselves interesting within the context of furthering our understanding of the adaptive process, the statistical approach presented here additionally represents a robust methodology for characterizing the DFE in future NGS experimental data sets.
Understanding the adaptive capacity of systems helps to plan for cities that are more resilient.
Understanding the melting potential of non-thermometers should aid in understanding the adaptive features of RNA thermometer sequences.
This apparently illustrates the formidable challenge to understanding the adaptive evolution of complex trait variation.
Understanding the adaptive significance of such variation is of relevance that needs further experimentation.
This modeling in rodents could be used in future studies in combination with biological tools for enhancing our understanding of the adaptive processes that occur during physical training.
Examples of adaptive radiations suggest that either chance or adaptation can be the dominant factor in shaping the adaptive process and the resulting adaptive radiations [7], [8].
This comment underscores the extreme deficiencies in understanding the process of adaptive radiation.
