{"title":"使用遗传算法对仅在感兴趣的序列子集中表示的基序进行推理","authors":"Jeffrey A. Thompson, C. Congdon","doi":"10.1109/BIBMW.2011.6112539","DOIUrl":null,"url":null,"abstract":"In this work, we present GAMID, and extension of GAMI. GAMID is designed to be used for motif inference in noncoding DNA for co-expressed genes or for divergent species. In these cases, we would like to allow the inferred motif to be present in only a subset of the input data. This paper describes the approach and presents preliminary results.","PeriodicalId":6345,"journal":{"name":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","volume":"14 1","pages":"1005-1005"},"PeriodicalIF":0.0000,"publicationDate":"2011-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Using genetic algorithms for the inference of motifs that are represented in only a subset of sequences of interest\",\"authors\":\"Jeffrey A. Thompson, C. Congdon\",\"doi\":\"10.1109/BIBMW.2011.6112539\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, we present GAMID, and extension of GAMI. GAMID is designed to be used for motif inference in noncoding DNA for co-expressed genes or for divergent species. In these cases, we would like to allow the inferred motif to be present in only a subset of the input data. This paper describes the approach and presents preliminary results.\",\"PeriodicalId\":6345,\"journal\":{\"name\":\"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)\",\"volume\":\"14 1\",\"pages\":\"1005-1005\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2011-11-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/BIBMW.2011.6112539\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2011 IEEE International Conference on Bioinformatics and Biomedicine Workshops (BIBMW)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/BIBMW.2011.6112539","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Using genetic algorithms for the inference of motifs that are represented in only a subset of sequences of interest
In this work, we present GAMID, and extension of GAMI. GAMID is designed to be used for motif inference in noncoding DNA for co-expressed genes or for divergent species. In these cases, we would like to allow the inferred motif to be present in only a subset of the input data. This paper describes the approach and presents preliminary results.