{"title":"GenePC和ASPIC整合基因预测与表达序列比对预测替代转录本","authors":"T. Alioto, R. Guigó, E. Picardi, G. Pesole","doi":"10.1142/9781848161092_0037","DOIUrl":null,"url":null,"abstract":"We have developed a generic framework for combining introns from genomicly aligned expressed–sequence–tag clusters with a set of exon predictions to produce alternative transcript predictions. Our current implementation uses ASPIC to generate alternative transcripts from EST mappings. Introns from ASPIC and a set of gene predictions from many diverse gene prediction programs are given to the gene prediction combiner GenePC which then generates alternative consensus splice forms. We evaluated our method on the ENCODE regions of the human genome. In general we see a marked improvement in transcript-level sensitivity due to the fact that more than one transcript per gene may now be predicted. GenePC, which alone is highly specific at the transcript level, balances the lower specificity of ASPIC.","PeriodicalId":74513,"journal":{"name":"Proceedings of the ... Asia-Pacific bioinformatics conference","volume":"29 1","pages":"363-372"},"PeriodicalIF":0.0000,"publicationDate":"2007-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"GenePC and ASPIC Integrate Gene Predictions with Expressed Sequence Alignments To Predict Alternative Transcripts\",\"authors\":\"T. Alioto, R. Guigó, E. Picardi, G. Pesole\",\"doi\":\"10.1142/9781848161092_0037\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"We have developed a generic framework for combining introns from genomicly aligned expressed–sequence–tag clusters with a set of exon predictions to produce alternative transcript predictions. Our current implementation uses ASPIC to generate alternative transcripts from EST mappings. Introns from ASPIC and a set of gene predictions from many diverse gene prediction programs are given to the gene prediction combiner GenePC which then generates alternative consensus splice forms. We evaluated our method on the ENCODE regions of the human genome. In general we see a marked improvement in transcript-level sensitivity due to the fact that more than one transcript per gene may now be predicted. GenePC, which alone is highly specific at the transcript level, balances the lower specificity of ASPIC.\",\"PeriodicalId\":74513,\"journal\":{\"name\":\"Proceedings of the ... Asia-Pacific bioinformatics conference\",\"volume\":\"29 1\",\"pages\":\"363-372\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2007-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of the ... Asia-Pacific bioinformatics conference\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1142/9781848161092_0037\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the ... Asia-Pacific bioinformatics conference","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1142/9781848161092_0037","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
GenePC and ASPIC Integrate Gene Predictions with Expressed Sequence Alignments To Predict Alternative Transcripts
We have developed a generic framework for combining introns from genomicly aligned expressed–sequence–tag clusters with a set of exon predictions to produce alternative transcript predictions. Our current implementation uses ASPIC to generate alternative transcripts from EST mappings. Introns from ASPIC and a set of gene predictions from many diverse gene prediction programs are given to the gene prediction combiner GenePC which then generates alternative consensus splice forms. We evaluated our method on the ENCODE regions of the human genome. In general we see a marked improvement in transcript-level sensitivity due to the fact that more than one transcript per gene may now be predicted. GenePC, which alone is highly specific at the transcript level, balances the lower specificity of ASPIC.