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Development of a novel mitochondrial cleavage site predictor
http://hdl.handle.net/2261/52244
http://hdl.handle.net/2261/522440b03516d-aa10-4057-819f-884fcd91f4a5
| 名前 / ファイル | ライセンス | アクション |
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本文(fulltext) (1.8 MB)
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要旨(summary) (70.4 kB)
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| Item type | 学位論文 / Thesis or Dissertation(1) | |||||
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| 公開日 | 2012-10-10 | |||||
| タイトル | ||||||
| タイトル | Development of a novel mitochondrial cleavage site predictor | |||||
| 言語 | ||||||
| 言語 | eng | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Mitochondria | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | ミトコンドリア | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | Targeting signal | |||||
| キーワード | ||||||
| 主題Scheme | Other | |||||
| 主題 | clearage | |||||
| 資源タイプ | ||||||
| 資源タイプ識別子 | http://purl.org/coar/resource_type/c_46ec | |||||
| 資源タイプ | thesis | |||||
| 著者 |
Fukasawa, Yoshinori
× Fukasawa, Yoshinori |
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| 著者別名 | ||||||
| 識別子Scheme | WEKO | |||||
| 識別子 | 8267 | |||||
| 姓名 | 深沢, 嘉紀 | |||||
| 著者所属 | ||||||
| 値 | 東京大学大学院新領域創成科学研究科情報生命科学専攻 | |||||
| 著者所属 | ||||||
| 値 | Department of Computational Biology, Graduate School of Frontier Sciences, The University of Tokyo | |||||
| Abstract | ||||||
| 内容記述タイプ | Abstract | |||||
| 内容記述 | A large fraction of mitochondrial proteins are cleaved upon entry into the mitochondria, but prediction of this cleavage is still challenging. In chapter 1, I summarize necessary background to this important problem. In chapter 2, I demonstrate that my system, Mitochondrial matrix targeting Signal Predictor, MoiraiSP, which is based on data from recent proteomic studies can correctly identified the cleavage site of MPP more than 75% accuracy in both plant and yeast dataset. In chapter 3, I introduce sequence divergence, LD(i), as a novel feature for sorting signal prediction, and show that prediction can be improved by LD(i) than random, especially with other famous features such as physico-chemical propensities. In chapter 4, I present that MoiraiSP can treat a related problem, predicting mitochondrial matrix targeting signal by using only N-terminal sequence information such as net-charge or LD(i). MoiraiSP discriminates between cleaved and non-cleaved mitochondrial proteins with a success rate of 97% (plant) or 91% (yeast) by cross validation. Finally, in chapter 5, I discuss some novel candidates of protease substrates, which came up during my work. | |||||
| 書誌情報 | 発行日 2011-09-27 | |||||
| 日本十進分類法 | ||||||
| 主題Scheme | NDC | |||||
| 主題 | 463 | |||||
| 学位名 | ||||||
| 学位名 | 修士(科学) | |||||
| 学位 | ||||||
| 値 | master | |||||
| 研究科・専攻 | ||||||
| 値 | 新領域創成科学研究科情報生命科学専攻 | |||||
| 学位授与年月日 | ||||||
| 学位授与年月日 | 2011-09-27 | |||||
| 学位記番号 | ||||||
| 値 | 修創域第4109号 | |||||
