{"title":"单细胞转录组学揭示了pbmc和其他细胞类型特有的总结模式","authors":"Jingjie Xu, R. A. Shaikh, V. Brusic","doi":"10.1109/BIBM.2018.8621396","DOIUrl":null,"url":null,"abstract":"Single cell transcriptomics (SCT) reveals cellular patterns that are masked and hidden in bulk RNA experiments. We analyzed 100 human SCT data sets for summary patterns that quantify gene expression per individual cell as well as per gene. Peripheral Blood Mononuclear Cells (PBMCs) show patterns different to those of cancer cell lines, stem cells, embryonic stem cells and other cell types. The results indicate that classification methods based on overall properties of SCT data sets provide a useful first step for classification of cell types and subtypes.","PeriodicalId":108667,"journal":{"name":"2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","volume":"14 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Single Cell Transcriptomics Reveals Summary Patterns Specific for PBMCs and Other Cell Types\",\"authors\":\"Jingjie Xu, R. A. Shaikh, V. Brusic\",\"doi\":\"10.1109/BIBM.2018.8621396\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Single cell transcriptomics (SCT) reveals cellular patterns that are masked and hidden in bulk RNA experiments. We analyzed 100 human SCT data sets for summary patterns that quantify gene expression per individual cell as well as per gene. Peripheral Blood Mononuclear Cells (PBMCs) show patterns different to those of cancer cell lines, stem cells, embryonic stem cells and other cell types. The results indicate that classification methods based on overall properties of SCT data sets provide a useful first step for classification of cell types and subtypes.\",\"PeriodicalId\":108667,\"journal\":{\"name\":\"2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)\",\"volume\":\"14 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2018-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIBM.2018.8621396\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE International Conference on Bioinformatics and Biomedicine (BIBM)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBM.2018.8621396","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Single Cell Transcriptomics Reveals Summary Patterns Specific for PBMCs and Other Cell Types
Single cell transcriptomics (SCT) reveals cellular patterns that are masked and hidden in bulk RNA experiments. We analyzed 100 human SCT data sets for summary patterns that quantify gene expression per individual cell as well as per gene. Peripheral Blood Mononuclear Cells (PBMCs) show patterns different to those of cancer cell lines, stem cells, embryonic stem cells and other cell types. The results indicate that classification methods based on overall properties of SCT data sets provide a useful first step for classification of cell types and subtypes.
求助内容：
应助结果提醒方式：
京公网安备 11010802042870号
