<span>Review your credit report annually to ensure information contained is accurate. Immediately contact all three credit bureaus to correct mistakes. Have revolving and installment accounts that are kept current. Pay debt on time to prevent derogatory information from being reported.</span>
The brain loses 5-10 percent of its weight between the ages 20 & 90.
We need options :) but stem cells are a amazing type of cells that are able to develop into many different types of cells <span>First, they are unspecialized cells capable of renewing themselves through </span>cell division<span>, sometimes after long periods of inactivity. Second, under certain physiologic or experimental conditions, they can be induced to become tissue- or organ-specific cells with special functions. In some organs, such as the gut and bone marrow, stem cells regularly divide to repair and replace worn out or damaged tissues. In other organs, however, such as the pancreas and the heart, stem cells only divide under special conditions.</span>
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Enzymes are biological catalysts. Catalysts lower the activation energy for reactions. The lower the activation energy for a reaction, the faster the rate. Thus enzymes speed up reactions by lowering activation energy.
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Results
We systematically analyze and compare how different modelling methodologies can be used to describe translation. We define various statistically equivalent codon-based simulation algorithms and analyze the importance of the update rule in determining the steady state, an aspect often neglected. Then a novel probabilistic Boolean network (PBN) model is proposed for modelling translation, which enjoys an exact numerical solution. This solution matches those of numerical simulation from other methods and acts as a complementary tool to analytical approximations and simulations. The advantages and limitations of various codon-based models are compared, and illustrated by examples with real biological complexities such as slow codons, premature termination and feedback regulation. Our studies reveal that while different models gives broadly similiar trends in many cases, important differences also arise and can be clearly seen, in the dependence of the translation rate on different parameters. Furthermore, the update rule affects the steady state solution.
Conclusions
The codon-based models are based on different levels of abstraction. Our analysis suggests that a multiple model approach to understanding translation allows one to ascertain which aspects of the conclusions are robust with respect to the choice of modelling methodology, and when (and why) important differences may arise. This approach also allows for an optimal use of analysis tools, which is especially important when additional complexities or regulatory mechanisms are included. This approach can provide a robust platform for dissecting translation, and results in an improved predictive framework for applications in systems and synthetic biology.
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