空间解析转录组数据分析的统计方法

Bioprocess technology Pub Date : 2023-01-01 DOI:10.12677/bp.2023.131008

琳王

{"title":"空间解析转录组数据分析的统计方法","authors":"琳王","doi":"10.12677/bp.2023.131008","DOIUrl":null,"url":null,"abstract":"In recent years, the development of spatial transcriptomics has enabled multiple analyses of cell transcriptome and its spatial location. With the increasing ability and efficiency of experimental technology, the requirement of developing analytical methods has gradually emerged. Techniques for generating Spatially Resolved Transcriptome (SRT) data are rapidly improving and being applied to study a variety of biological tissues. It is critical to study how spatially localized gene ex-王琳，赵桂华","PeriodicalId":77040,"journal":{"name":"Bioprocess technology","volume":"34 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Statistical Methods for Spatially Re-solved Transcriptomic Data Analysis\",\"authors\":\"琳王\",\"doi\":\"10.12677/bp.2023.131008\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In recent years, the development of spatial transcriptomics has enabled multiple analyses of cell transcriptome and its spatial location. With the increasing ability and efficiency of experimental technology, the requirement of developing analytical methods has gradually emerged. Techniques for generating Spatially Resolved Transcriptome (SRT) data are rapidly improving and being applied to study a variety of biological tissues. It is critical to study how spatially localized gene ex-王琳，赵桂华\",\"PeriodicalId\":77040,\"journal\":{\"name\":\"Bioprocess technology\",\"volume\":\"34 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Bioprocess technology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.12677/bp.2023.131008\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Bioprocess technology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.12677/bp.2023.131008","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

查看原文本刊更多论文

Statistical Methods for Spatially Re-solved Transcriptomic Data Analysis

In recent years, the development of spatial transcriptomics has enabled multiple analyses of cell transcriptome and its spatial location. With the increasing ability and efficiency of experimental technology, the requirement of developing analytical methods has gradually emerged. Techniques for generating Spatially Resolved Transcriptome (SRT) data are rapidly improving and being applied to study a variety of biological tissues. It is critical to study how spatially localized gene ex-王琳，赵桂华

求助全文

通过发布文献求助，成功后即可免费获取论文全文。去求助

来源期刊

Bioprocess technology

自引率

0.00%

发文量