{"title":"无家族重排对基因同源推断的潜力。","authors":"Diego P Rubert, Daniel Doerr, Marília D V Braga","doi":"10.1142/S021972002140014X","DOIUrl":null,"url":null,"abstract":"<p><p>Recently, we proposed an efficient ILP formulation [Rubert DP, Martinez FV, Braga MDV, Natural family-free genomic distance, <i>Algorithms Mol Biol</i> <b>16</b>:4, 2021] for exactly computing the rearrangement distance of two genomes in a <i>family-free</i> setting. In such a setting, neither prior classification of genes into families, nor further restrictions on the genomes are imposed. Given two genomes, the mentioned ILP computes an optimal matching of the genes taking into account simultaneously local mutations, given by gene similarities, and large-scale genome rearrangements. Here, we explore the potential of using this ILP for inferring groups of orthologs across several species. More precisely, given a set of genomes, our method first computes all pairwise optimal gene matchings, which are then integrated into gene families in the second step. Our approach is implemented into a pipeline incorporating the pre-computation of gene similarities. It can be downloaded from gitlab.ub.uni-bielefeld.de/gi/FFGC. We obtained promising results with experiments on both simulated and real data.</p>","PeriodicalId":48910,"journal":{"name":"Journal of Bioinformatics and Computational Biology","volume":"19 6","pages":"2140014"},"PeriodicalIF":0.9000,"publicationDate":"2021-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"The potential of family-free rearrangements towards gene orthology inference.\",\"authors\":\"Diego P Rubert, Daniel Doerr, Marília D V Braga\",\"doi\":\"10.1142/S021972002140014X\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>Recently, we proposed an efficient ILP formulation [Rubert DP, Martinez FV, Braga MDV, Natural family-free genomic distance, <i>Algorithms Mol Biol</i> <b>16</b>:4, 2021] for exactly computing the rearrangement distance of two genomes in a <i>family-free</i> setting. In such a setting, neither prior classification of genes into families, nor further restrictions on the genomes are imposed. Given two genomes, the mentioned ILP computes an optimal matching of the genes taking into account simultaneously local mutations, given by gene similarities, and large-scale genome rearrangements. Here, we explore the potential of using this ILP for inferring groups of orthologs across several species. More precisely, given a set of genomes, our method first computes all pairwise optimal gene matchings, which are then integrated into gene families in the second step. Our approach is implemented into a pipeline incorporating the pre-computation of gene similarities. It can be downloaded from gitlab.ub.uni-bielefeld.de/gi/FFGC. We obtained promising results with experiments on both simulated and real data.</p>\",\"PeriodicalId\":48910,\"journal\":{\"name\":\"Journal of Bioinformatics and Computational Biology\",\"volume\":\"19 6\",\"pages\":\"2140014\"},\"PeriodicalIF\":0.9000,\"publicationDate\":\"2021-12-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Bioinformatics and Computational Biology\",\"FirstCategoryId\":\"99\",\"ListUrlMain\":\"https://doi.org/10.1142/S021972002140014X\",\"RegionNum\":4,\"RegionCategory\":\"生物学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2021/11/13 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q4\",\"JCRName\":\"MATHEMATICAL & COMPUTATIONAL BIOLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Bioinformatics and Computational Biology","FirstCategoryId":"99","ListUrlMain":"https://doi.org/10.1142/S021972002140014X","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2021/11/13 0:00:00","PubModel":"Epub","JCR":"Q4","JCRName":"MATHEMATICAL & COMPUTATIONAL BIOLOGY","Score":null,"Total":0}
The potential of family-free rearrangements towards gene orthology inference.
Recently, we proposed an efficient ILP formulation [Rubert DP, Martinez FV, Braga MDV, Natural family-free genomic distance, Algorithms Mol Biol16:4, 2021] for exactly computing the rearrangement distance of two genomes in a family-free setting. In such a setting, neither prior classification of genes into families, nor further restrictions on the genomes are imposed. Given two genomes, the mentioned ILP computes an optimal matching of the genes taking into account simultaneously local mutations, given by gene similarities, and large-scale genome rearrangements. Here, we explore the potential of using this ILP for inferring groups of orthologs across several species. More precisely, given a set of genomes, our method first computes all pairwise optimal gene matchings, which are then integrated into gene families in the second step. Our approach is implemented into a pipeline incorporating the pre-computation of gene similarities. It can be downloaded from gitlab.ub.uni-bielefeld.de/gi/FFGC. We obtained promising results with experiments on both simulated and real data.
期刊介绍:
The Journal of Bioinformatics and Computational Biology aims to publish high quality, original research articles, expository tutorial papers and review papers as well as short, critical comments on technical issues associated with the analysis of cellular information.
The research papers will be technical presentations of new assertions, discoveries and tools, intended for a narrower specialist community. The tutorials, reviews and critical commentary will be targeted at a broader readership of biologists who are interested in using computers but are not knowledgeable about scientific computing, and equally, computer scientists who have an interest in biology but are not familiar with current thrusts nor the language of biology. Such carefully chosen tutorials and articles should greatly accelerate the rate of entry of these new creative scientists into the field.