| Chapter title |
Comparative Genomics for Prokaryotes
|
|---|---|
| Chapter number | 3 |
| Book title |
Comparative Genomics
|
| Published in |
Methods in molecular biology, January 2018
|
| DOI | 10.1007/978-1-4939-7463-4_3 |
| Pubmed ID | |
| Book ISBNs |
978-1-4939-7461-0, 978-1-4939-7463-4
|
| Authors |
João C. Setubal, Nalvo F. Almeida, Alice R. Wattam |
| Abstract |
Bacteria and archaea, collectively known as prokaryotes, have in general genomes that are much smaller than those of eukaryotes. As a result, thousands of these genomes have been sequenced. In prokaryotes, gene architecture lacks the intron-exon structure of eukaryotic genes (with an occasional exception). These two facts mean that there is an abundance of data for prokaryotic genomes, and that they are easier to study than the more complex eukaryotic genomes. In this chapter, we provide an overview of genome comparison tools that have been developed primarily (sometimes exclusively) for prokaryotic genomes. We cover methods that use only the DNA sequences, methods that use only the gene content, and methods that use both data types. |
X Demographics
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 20% |
| Unknown | 4 | 80% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Scientists | 3 | 60% |
| Members of the public | 2 | 40% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 91 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 18 | 20% |
| Student > Master | 13 | 14% |
| Student > Bachelor | 12 | 13% |
| Researcher | 10 | 11% |
| Student > Doctoral Student | 3 | 3% |
| Other | 8 | 9% |
| Unknown | 27 | 30% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 25 | 27% |
| Biochemistry, Genetics and Molecular Biology | 23 | 25% |
| Unspecified | 4 | 4% |
| Computer Science | 4 | 4% |
| Immunology and Microbiology | 3 | 3% |
| Other | 5 | 5% |
| Unknown | 27 | 30% |