{"title":"pLoc_bal-mPlant是一个强大的人工智能工具，用于预测植物蛋白的亚细胞定位，完全基于它们的序列信息","authors":"K. Chou","doi":"10.15761/jscrm.1000138","DOIUrl":null,"url":null,"abstract":"Recently a very useful web-server, or AI (Artificial Intelligence) tool, has been developed for predicting the subcellular localization of plant proteins purely according to their information for the multilabel systems [1], in which a same protein may appear or travel between two or more locations and hence its ID (identification) needs two or more labels as well, namely the “multi-label mark” [2].","PeriodicalId":318869,"journal":{"name":"Journal of Stem Cell Research and Medicine","volume":"1 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"9","resultStr":"{\"title\":\"The pLoc_bal-mPlant is a powerful artificial intelligence tool for predicting the subcellular localization of plant proteins purely based on their sequence information\",\"authors\":\"K. Chou\",\"doi\":\"10.15761/jscrm.1000138\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Recently a very useful web-server, or AI (Artificial Intelligence) tool, has been developed for predicting the subcellular localization of plant proteins purely according to their information for the multilabel systems [1], in which a same protein may appear or travel between two or more locations and hence its ID (identification) needs two or more labels as well, namely the “multi-label mark” [2].\",\"PeriodicalId\":318869,\"journal\":{\"name\":\"Journal of Stem Cell Research and Medicine\",\"volume\":\"1 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1900-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"9\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Stem Cell Research and Medicine\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.15761/jscrm.1000138\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Stem Cell Research and Medicine","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.15761/jscrm.1000138","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The pLoc_bal-mPlant is a powerful artificial intelligence tool for predicting the subcellular localization of plant proteins purely based on their sequence information
Recently a very useful web-server, or AI (Artificial Intelligence) tool, has been developed for predicting the subcellular localization of plant proteins purely according to their information for the multilabel systems [1], in which a same protein may appear or travel between two or more locations and hence its ID (identification) needs two or more labels as well, namely the “multi-label mark” [2].
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