Chapter title |
Construction of Functional Gene Networks Using Phylogenetic Profiles.
|
---|---|
Chapter number | 5 |
Book title |
Bioinformatics
|
Published in |
Methods in molecular biology, January 2017
|
DOI | 10.1007/978-1-4939-6613-4_5 |
Pubmed ID | |
Book ISBNs |
978-1-4939-6611-0, 978-1-4939-6613-4
|
Authors |
Junha Shin, Insuk Lee |
Editors |
Jonathan M. Keith |
Abstract |
Functional constraints between genes display similar patterns of gain or loss during speciation. Similar phylogenetic profiles, therefore, can be an indication of a functional association between genes. The phylogenetic profiling method has been applied successfully to the reconstruction of gene pathways and the inference of unknown gene functions. This method requires only sequence data to generate phylogenetic profiles. This method therefore has the potential to take advantage of the recent explosion in available sequence data to reveal a significant number of functional associations between genes. Since the initial development of phylogenetic profiling, many modifications to improve this method have been proposed, including improvements in the measurement of profile similarity and the selection of reference species. Here, we describe the existing methods of phylogenetic profiling for the inference of functional associations and discuss their technical limitations and caveats. |
X Demographics
Geographical breakdown
Country | Count | As % |
---|---|---|
United States | 1 | 100% |
Demographic breakdown
Type | Count | As % |
---|---|---|
Members of the public | 1 | 100% |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
Unknown | 5 | 100% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 1 | 20% |
Researcher | 1 | 20% |
Student > Postgraduate | 1 | 20% |
Unknown | 2 | 40% |
Readers by discipline | Count | As % |
---|---|---|
Biochemistry, Genetics and Molecular Biology | 1 | 20% |
Computer Science | 1 | 20% |
Agricultural and Biological Sciences | 1 | 20% |
Unknown | 2 | 40% |