PseudoDomain: identification of processed pseudogenes based on protein domain classification
Authors: 
Yuan Zhang, Yanni SunAuthors Info & Claims
Pages 178 - 185
Abstract
Pseudogenes are dysfunctional DNA sequences that share sequence similarities with functional genes. Accurate identification of pseudogenes is important to understand biological and evolutionary histories of genomes and genes. Most existing pseudogene identification tools rely on homology search between genomic sequences and annotated proteins of the same genome. However, when accurate annotations of the genome of interest are not available, these tools will not be able to provide reliable pseudogene identification. In this work, we introduce a new pseudogene identification tool named PseudoDomain, which is designed to accurately identify processed pseudogenes in genomes with or without gene annotations. PseudoDomain uses profile Hidden Markov Model-based homology search between genomic sequences and protein domain families, which are conserved in a large number of proteins. Experimental results show that our method is able to effectively identify processed pseudogenes with high sensitivity and low false positive rate. In addition, it can accurately predict the number and positions of frameshifts within putative pseudogenes. The source codes of PseudoDomain are available at http://sourceforge.net/projects/pseudodomain/.
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- PseudoDomain: identification of processed pseudogenes based on protein domain classification
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Published In
October 2012
725 pages
ISBN:9781450316705
DOI:10.1145/2382936
- General Chair:
- Sanjay Ranka,
- Program Chairs:
- Tamer Kahveci,
- Mona Singh
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Published: 07 October 2012
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