Answer: strengths: the diagram is easy to read and understand . It shows simply how the introns splice out to form messenger RNA.it also shows where the transcription and translation start.
Limitations: the diagram does not show that the process starts with double helix DNA. The process of translation doesn’t not show that the messenger RNA first connects amino acids to become proteins, the role of the ribosomes in the process , or that the process requires three types of RNA.
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.
By definition, a chaparral ecosystem is mostly located in the south of the United States wherein it mainly comprises the mountain ranges of Sierra Nevada. In addition to that, biotic characteristics of these chaparrals include having abiotic factos such as wet winters and dry summers that sometimes cause wildfires.
