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タイトル: Proteome compression via protein domain compositions.
著者: Hayashida, Morihiro  KAKEN_id
Ruan, Peiying
Akutsu, Tatsuya  kyouindb  KAKEN_id  orcid https://orcid.org/0000-0001-9763-797X (unconfirmed)
著者名の別形: 林田, 守広
阿久津, 達也
キーワード: Grammar-based compression
Protein domain composition
Integer linear programming
発行日: 1-Jun-2014
出版者: Elsevier Inc.
誌名: Methods
巻: 67
号: 3
開始ページ: 380
終了ページ: 385
抄録: In this paper, we study domain compositions of proteins via compression of whole proteins in an organism for the sake of obtaining the entropy that the individual contains. We suppose that a protein is a multiset of domains. Since gene duplication and fusion have occurred through evolutionary processes, the same domains and the same compositions of domains appear in multiple proteins, which enables us to compress a proteome by using references to proteins for duplicated and fused proteins. Such a network with references to at most two proteins is modeled as a directed hypergraph. We propose a heuristic approach by combining the Edmonds algorithm and an integer linear programming, and apply our procedure to 14 proteomes of Dictyostelium discoideum, Escherichia coli, Saccharomyces cerevisiae, Schizosaccharomyces pombe, Caenorhabditis elegans, Drosophila melanogaster, Arabidopsis thaliana, Oryza sativa, Danio rerio, Xenopus laevis, Gallus gallus, Mus musculus, Pan troglodytes, and Homo sapiens. The compressed size using both of duplication and fusion was smaller than that using only duplication, which suggests the importance of fusion events in evolution of a proteome.
著作権等: © 2014 Elsevier Inc.
This is not the published version. Please cite only the published version.
この論文は出版社版でありません。引用の際には出版社版をご確認ご利用ください。
URI: http://hdl.handle.net/2433/188898
DOI(出版社版): 10.1016/j.ymeth.2014.01.012
PubMed ID: 24486717
出現コレクション:学術雑誌掲載論文等

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