Immunosignature Screening for Multiple Cancer Subtypes Based on Expression Rule
文献类型：期刊论文
| 作者 | Chen, Lei1,2,3; Cai, Yu-Dong1; Pan, XiaoYong4,5; Zeng, Tao6; Zhang, Yu-Hang7; Huang, Tao7; Zhang, YunHua8; , |
| 刊名 | FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY
 |
| 出版日期 | 2019 |
| 卷号 | 7期号:-页码:370 |
| 关键词 | cancer subtype expression rule immunosignature multi-class classification feature selection |
| ISSN号 | 2296-4185 |
| DOI | 10.3389/fbioe.2019.00370 |
| 文献子类 | Article |
| 英文摘要 | Liquid biopsy (i.e., fluid biopsy) involves a series of clinical examination approaches. Monitoring of cancer immunological status by the "immunosignature" of patients presents a novel method for tumor-associated liquid biopsy. The major work content and the core technological difficulties for the monitoring of cancer immunosignature are the recognition of cancer-related immune-activating antigens by high-throughput screening approaches. Currently, one key task of immunosignature-based liquid biopsy is the qualitative and quantitative identification of typical tumor-specific antigens. In this study, we reused two sets of peptide microarray data that detected the expression level of potential antigenic peptides derived from tumor tissues to avoid the detection differences induced by chip platforms. Several machine learning algorithms were applied on these two sets. First, the Monte Carlo Feature Selection (MCFS) method was used to analyze features in two sets. A feature list was obtained according to the MCFS results on each set. Second, incremental feature selection method incorporating one classification algorithm (support vector machine or random forest) followed to extract optimal features and construct optimal classifiers. On the other hand, the repeated incremental pruning to produce error reduction, a rule learning algorithm, was applied on key features yielded by the MCFS method to extract quantitative rules for accurate cancer immune monitoring and pathologic diagnosis. Finally, obtained key features and quantitative rules were extensively analyzed. |
| 学科主题 | Cell Biology |
| WOS关键词 | CELL ; IDENTIFICATION ; ANGIOGENESIS ; GENES ; TRANSPLANTATION ; METHYLATION ; PREDICTION ; DIAGNOSIS ; PATHWAYS ; NETWORK |
| 语种 | 英语 |
| CSCD记录号 | CSCD:31850330 |
| WOS记录号 | WOS:000502734900001 |
| 出版者 | FRONTIERS MEDIA SA |
| 版本 | 出版稿 |
| 源URL | [http://202.127.25.144/handle/331004/1158]  |
| 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.Shanghai Univ, Sch Life Sci, Shanghai, Peoples R China; 2.Shanghai Maritime Univ, Coll Informat Engn, Shanghai, Peoples R China; 3.East China Normal Univ, Shanghai Key Lab Pure Math & Math Practice PMMP, Shanghai, Peoples R China; 4.Shanghai Jiao Tong Univ, Inst Image Proc & Pattern Recognit, Key Lab Syst Control & Informat Proc, Minist Educ China, Shanghai, Peoples R China; 5.Univ Ghent, IDLab, Dept Elect & Informat Syst, Ghent, Belgium; 6.Chinese Acad Sci, Inst Biochem & Cell Biol, Key Lab Syst Biol, Shanghai, Peoples R China; 7.Chinese Acad Sci, Shanghai Inst Nutr & Hlth, Shanghai Inst Biol Sci, Shanghai, Peoples R China; 8.Anhui Agr Univ, Anhui Prov Key Lab Farmland Ecol Conservat & Poll, Sch Resources & Environm, Hefei, Anhui, Peoples R China, |
| 推荐引用方式 GB/T 7714 | Chen, Lei,Cai, Yu-Dong,Pan, XiaoYong,et al. Immunosignature Screening for Multiple Cancer Subtypes Based on Expression Rule[J]. FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY,2019,7(-):370. |
| APA | Chen, Lei.,Cai, Yu-Dong.,Pan, XiaoYong.,Zeng, Tao.,Zhang, Yu-Hang.,...&,.(2019).Immunosignature Screening for Multiple Cancer Subtypes Based on Expression Rule.FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY,7(-),370. |
| MLA | Chen, Lei,et al."Immunosignature Screening for Multiple Cancer Subtypes Based on Expression Rule".FRONTIERS IN BIOENGINEERING AND BIOTECHNOLOGY 7.-(2019):370. |
入库方式： OAI收割
来源：上海营养与健康研究所
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