Journal of Microbiology and Immunology

Genomics Microbial

Citations are important for a journal to get impact factor. Impact factor is a measure reflecting the average number of citations to recent articles published in the journal. The impact of the journal is influenced by impact factor, the journals with high impact factor are considered more important than those with lower ones. Impact factor plays a major role for the particular journal. Journal with higher impact factor is considered to be more important than other ones. Impact factor can be calculated as average number of citation divided by recent cited articles published in 2 years. Microbial genomes encompass all chromosomal and extra chromosomal genetic material. The study of microbial genomes helps us to better understand the broader biology of bacteria, and how their genetic composition contributes to their tangible characteristics. The study of genomics is also important to infer the evolution of bacteria. Bacteria often evolve not just through small, single nucleotide level changes but through quantum evolutionary events. These include through the transfer of plasmids between species and also the transposition of large genetic elements within single cells. Understanding these processes allows us to determine the origins of bacteria and map the transfer of genes such as those conferring antibiotic resistance. In the years preceding the development of full genome sequencing techniques we were restricted to studying microbial genomes in the lab using techniques such as PFGE. Their method, termed Sanger Sequencing was a platform for innovation in the field of DNA sequencing, and we now have methods for sequencing entire bacterial genomes with relative ease. Whole genome sequencing produces immense amounts of data from which we can derive a catalogue of important information. From the need to analyse this data, the field of bioinformatics has flourished and become an integral part of genetics research. Bioinformatics is the use of computing technologies to manage and analyse biological data. The huge amounts of genomic data produced through DNA sequencing can often be very confusing and difficult to analyse.

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