Predicting Citrullination Sites in Protein Sequences Using mRMR Method and Random Forest Algorithm
文献类型：期刊论文
| 作者 | Zhang, Qing2; Sun, Xijun2; Wang, ShaoPeng2; Wan, SiBao2; Cai, Yu-Dong2; Zhang, Yu-Hang3; Feng, Kaiyan1; Lu, Lin4; , |
| 刊名 | COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING
 |
| 出版日期 | 2017 |
| 卷号 | 20期号:2页码:164-173 |
| 关键词 | Post-translational modification citrullination site maximum relevance minimum redundancy random forest |
| ISSN号 | 1386-2073 |
| DOI | 10.2174/1386207319666161227124350 |
| 文献子类 | Article |
| 英文摘要 | Background: As one of essential post-translational modifications (PTMs), the citrullination or deimination on an arginine residue would change the molecular weight and electrostatic charge of its side-chain. And it has been found that the citrullination in protein sequences was catalyzed by a type of Ca2+-dependent enzyme family called peptidylarginine deiminase (PAD), which include five isotypes: PAD1, 2, 3, 4/5, and 6. Citrullinated proteins participate in many biological processes, e.g. the citrullination of myelin basic protein (MBP) assists the early development of central nervous system. However, abnormal modifications on citrullinated proteins would also lead to some severe human diseases including multiple sclerosis and rheumatoid arthritis. Objective: Therefore, it is necessary and important to identify the citrullination sites in protein sequences. The information about the location of citrulliantion sites in protein sequences will be useful to investigate the molecular functions and disease mechanisms related to citrullinated proteins. Materials and Methods: In this study, we investigated the peptide segments that contain the citrullination sites in the centers, which were encoded into numeric digits from four aspects. Thus, we yielded a training set with 116 positive samples and 232 negative samples. Then, a reliable feature selection technique, called maximum-relevance-minimum-redundancy (mRMR), was applied to analyze these features, and four algorithms, including random forest (RF), Dagging, nearest neighbor algorithm (NNA), and support vector machine (SVM), together with the incremental feature selection (IFS) method were adopted to extract important features. Results: Finally an optimal classifier derived from RF algorithm was constructed to predict citrullination sites. 44 most prominent features were comprehensively analyzed and their biological characteristics in citrullination catalysis were also revealed. Conclusion: We believed that the biological features obtained in this pioneering work would provide some useful insights into the formation and function of citrullination and the optimal classifier could be a useful tool to identify citrullination sites in protein sequences. |
| 学科主题 | Biochemistry & Molecular Biology ; Chemistry ; Pharmacology & Pharmacy |
| WOS关键词 | FEATURE-SELECTION ; POSTTRANSLATIONAL MODIFICATIONS ; PEPTIDYLARGININE DEIMINASES ; MOLECULAR FRAGMENTS ; MULTIPLE-SCLEROSIS ; GENE ONTOLOGY ; EXPRESSION ; DISORDER ; CLASSIFICATION ; PATHOGENESIS |
| 语种 | 英语 |
| WOS记录号 | WOS:000402823500011 |
| 出版者 | BENTHAM SCIENCE PUBL LTD |
| 版本 | 出版稿 |
| 源URL | [http://202.127.25.144/handle/331004/499]  |
| 专题 | 中国科学院上海生命科学研究院营养科学研究所 |
| 作者单位 | 1.Guangdong AIB Polytech, Dept Comp Sci, Guangzhou, Guangdong, Peoples R China; 2.Shanghai Univ, Sch Life Sci, Shanghai 200444, Peoples R China; 3.Chinese Acad Sci, Shanghai Inst Biol Sci, Inst Hlth Sci, Shanghai 200031, Peoples R China; 4.Columbia Univ, Med Ctr, Dept Radiol, New York, NY 10032 USA, |
| 推荐引用方式 GB/T 7714 | Zhang, Qing,Sun, Xijun,Wang, ShaoPeng,et al. Predicting Citrullination Sites in Protein Sequences Using mRMR Method and Random Forest Algorithm[J]. COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING,2017,20(2):164-173. |
| APA | Zhang, Qing.,Sun, Xijun.,Wang, ShaoPeng.,Wan, SiBao.,Cai, Yu-Dong.,...&,.(2017).Predicting Citrullination Sites in Protein Sequences Using mRMR Method and Random Forest Algorithm.COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING,20(2),164-173. |
| MLA | Zhang, Qing,et al."Predicting Citrullination Sites in Protein Sequences Using mRMR Method and Random Forest Algorithm".COMBINATORIAL CHEMISTRY & HIGH THROUGHPUT SCREENING 20.2(2017):164-173. |
入库方式： OAI收割
来源：上海营养与健康研究所
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