| Chapter title |
Inferring orthology and paralogy.
|
|---|---|
| Chapter number | 9 |
| Book title |
Evolutionary Genomics
|
| Published in |
Methods in molecular biology, February 2012
|
| DOI | 10.1007/978-1-61779-582-4_9 |
| Pubmed ID | |
| Book ISBNs |
978-1-61779-581-7, 978-1-61779-582-4
|
| Authors |
Adrian M. Altenhoff, Christophe Dessimoz, Altenhoff, Adrian M., Dessimoz, Christophe |
| Editors |
Maria Anisimova |
| Abstract |
The distinction between orthologs and paralogs, genes that started diverging by speciation versus duplication, is relevant in a wide range of contexts, most notably phylogenetic tree inference and protein function annotation. In this chapter, we provide an overview of the methods used to infer orthology and paralogy. We survey both graph-based approaches (and their various grouping strategies) and tree-based approaches, which solve the more general problem of gene/species tree reconciliation. We discuss conceptual differences among the various orthology inference methods and databases, and examine the difficult issue of verifying and benchmarking orthology predictions. Finally, we review typical applications of orthologous genes, groups, and reconciled trees and conclude with thoughts on future methodological developments. |
X Demographics
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|---|---|---|
| Brazil | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 3 | 3% |
| United States | 3 | 3% |
| Mexico | 2 | 2% |
| Sweden | 1 | <1% |
| Finland | 1 | <1% |
| Brazil | 1 | <1% |
| United Kingdom | 1 | <1% |
| Spain | 1 | <1% |
| Belgium | 1 | <1% |
| Other | 0 | 0% |
| Unknown | 96 | 87% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 29 | 26% |
| Researcher | 21 | 19% |
| Student > Master | 13 | 12% |
| Student > Bachelor | 9 | 8% |
| Professor | 6 | 5% |
| Other | 17 | 15% |
| Unknown | 15 | 14% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 55 | 50% |
| Biochemistry, Genetics and Molecular Biology | 20 | 18% |
| Computer Science | 7 | 6% |
| Engineering | 2 | 2% |
| Immunology and Microbiology | 1 | <1% |
| Other | 3 | 3% |
| Unknown | 22 | 20% |