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Comparative Genomics

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Attention for Chapter 6: Comparative Genome Annotation
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Chapter title
Comparative Genome Annotation
Chapter number 6
Book title
Comparative Genomics
Published in
Methods in molecular biology, January 2018
DOI 10.1007/978-1-4939-7463-4_6
Pubmed ID
Book ISBNs
978-1-4939-7461-0, 978-1-4939-7463-4
Authors

Stefanie König, Lars Romoth, Mario Stanke

Abstract

Newly sequenced genomes are being added to the tree of life at an unprecedented fast pace. Increasingly, such new genomes are phylogenetically close to previously sequenced and annotated genomes. In other cases, whole clades of closely related species or strains ought to be annotated simultaneously. Often, in subsequent studies differences between the closely related species or strains are in the focus of research when the shared gene structures prevail. We here review methods for comparative structural genome annotation. The reviewed methods include classical approaches such as the alignment of protein sequences or protein profiles against the genome and comparative gene prediction methods that exploit a genome alignment to annotate a target genome. Newer approaches such as the simultaneous annotation of multiple genomes are also reviewed. We discuss how the methods depend on the phylogenetic placement of genomes, give advice on the choice of methods, and examine the consistency between gene structure annotations in an example. Further, we provide practical advice on genome annotation in general.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 41 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 41 100%

Demographic breakdown

Readers by professional status Count As %
Student > Bachelor 9 22%
Student > Ph. D. Student 8 20%
Student > Master 7 17%
Student > Doctoral Student 2 5%
Other 2 5%
Other 4 10%
Unknown 9 22%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 14 34%
Agricultural and Biological Sciences 13 32%
Computer Science 2 5%
Pharmacology, Toxicology and Pharmaceutical Science 1 2%
Unknown 11 27%