<span>Nuc is short for nucleus</span>
A hammer is a lever, one of the six types of simple machines.
Explanation:
Oxygen is the answer. (option B)
Answer:
Explanation:
# Boys are four times more likely to be diagnosed with autism than girls.
# Most children were still being diagnosed after age 4, though autism can be reliably diagnosed as early as age 2.
# 31% of children with ASD have an intellectual disability (intelligence quotient [IQ] <70), 25% are in the borderline range (IQ 71–85), and 44% have IQ scores in the average to above average range (i.e., IQ >85).
# Autism affects all ethnic and socioeconomic groups.
# Minority groups tend to be diagnosed later and less often.
# Early intervention affords the best opportunity to support healthy development and deliver benefits across the lifespan.
# There is no medical detection for autism.
Answer:
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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