The saying ‘having a complete awareness about one’s self is important to personal growth’ is one that can also be applied in the field of computational genomics for a couple of reasons which will be explained below. But first, here is a brief explanation of computational genomics; the field of computational genomics is the use of computational analysis to analyze the data provided by the human genes, DNA and RNA.
As stated earlier, here is where parallels between the above saying and computational genomics are drawn. The analysis of genomic sequences provides man with a window into the thorough understanding of our past such as modern man’s relationship to the Neanderthals. This ability to discover the past and trace its effects to our future development has pushed the narrative of human evolution as well as helped scientist trace diseases, their cause and effect with the aim of predicting life cycles and developing vaccines to cure ancient ailments. Now, for those tasked with the responsibility of writing on computational genomics, this article is intended to serve as a topic directory as well as a tutorial on drafting a compare and contrast essay topic on the stated subject matter.
As earlier discussed, these topics are intended to provide you with some additional inspiration when searching for a compare and contrast essay topic to kick-start your assignment. The topic ‘Analyzing the roles of DNA and RNA in Computational Genomics’ will be drafted below to provide some guidelines on writing a compare and contrast essay.
In computational genomics, human genes, deoxyribonucleic acid (DNA) and ribonucleic acid (RNA) all play important roles both on their own as well as simultaneously in the analysis of genetic sequences. In this essay I intend to analyze the similarities and differences in the roles played by DNA and RNA in computational genomics.
First and foremost, I believe it is important to understand the concept of both factors for it plays an integral role in explaining their functions as well as the contrasting and similar features binding DNA and RNA together. DNA is a nucleic acid that contains the genetic instructions used in the development and functioning of all modern living organisms while RNA acts as the messenger which carries the DNA instructions needed to control the synthesis of protein in an organism. A simplified analogy of their symbiotic relationship is that of a computer’s operating system and internal programs that make the system function. Here, DNA is the operating system while RNA is the supporting program.
The similarities between both DNA and RNA are quite impressive, and scientists make use of these similarities in computational genomics in multiple ways. Some of these similarities are basically structured as can be seen from the fact that both RNA and DNA are made up of monomers called nucleotides. This structural similarity goes forward to include the fact that both factors contain pentose sugars and have the base pair of guanine and cytosine which are necessary for the cells to produce protein and are important factors in analyzing genes.
While the similarities between a cells’ DNA and RNA are generally contained towards the structural end, the contrasting features are more notable when the functions of both phosphoric acids are compared. Looking at their base function; DNA provides the biological blueprint that serve as guidelines for the human cell, it does this by producing and storing relevant information needed for the transfer of biological information within species and from one generation to the other. RNA on the other hand, also serves a different complementary function that is also quite important. It serves as the carrier of information for the DNA through the nucleus to the ribosome.
It is important to note that the important factor in computational genomics, genes, are found in small strands in the DNA and not the RNA. This means that DNA provides the most important data needed for computational genomics while the RNA provides complementary data to support the analytical process. In conclusion, the similarities and differences between DNA and RNA all work together to make computational genomics possible and this has led to scientific advances such as the sequencing of genes and understanding the pathology of diverse diseases and epidemics.
Here we come to the end of this article covering compare and contrast topics on the subject of computational genomics. Also recommended for extra reading are the follow-up articles covering 10 facts for a compare and contrast essay on computational genomics and the compare and contrast essay guide on computational genomics.
Raychaudhuri, S. (2006). Computational Text Analysis for Functional Genomics and Bioinformatics.
Zheng, Y., Li, X. and Hu, H. (2014). Computational discovery of feature patterns in Nucleosomal DNA sequences. Genomics, 104(2), pp.87-95.
Mao, Y. and Salavati, R. (2009). Genome-wide Computational Identification of Functional RNA Elements in Trypanosoma Brucei. BMC Genomics, 10(1), p.355.
Treangen, T. and Salzberg, S. (2011). Repetitive DNA and Next-generation Sequencing: Computational Challenges and Solutions. Nature Reviews Genetics.
Satellite Workshop on Comparative Genomics, Research in Computational Molecular Biology (2011). Journal of Computational Biology, 18(9), pp.1019-1021.
Nawrocki, E. and Eddy, S. (2013). Computational Identification of Functional RNA Homologs in Metagenomic data. RNA Biology, 10(7), pp.1170-1179.
Pareek, C. and Tretyn, A. (2011). Sequencing Technologies and Genome Sequencing. Journal of Applied Genetics, 52(4), pp.413-435.