{"title":"在果蝇3'非翻译区发现非编码RNA元件。","authors":"Cuncong Zhong, Justen Andrews, Shaojie Zhang","doi":"10.1504/IJBRA.2014.062996","DOIUrl":null,"url":null,"abstract":"<p><p>The Non-Coding RNA (ncRNA) elements in the 3' Untranslated Regions (3'-UTRs) are known to participate in the genes' post-transcriptional regulations. Inferring co-expression patterns of the genes through clustering these 3'-UTR ncRNA elements will provide invaluable insights for studying their biological functions. In this paper, we propose an improved RNA structural clustering pipeline. Benchmark of the new pipeline on Rfam data demonstrates over 10% performance improvements compared to the traditional hierarchical clustering pipeline. By applying the new clustering pipeline to 3'-UTRs of Drosophila melanogaster's genome, we have successfully identified 184 ncRNA clusters with 91.3% accuracy. One of these clusters corresponds to genes that are preferentially expressed in male Drosophila. Another cluster contains genes that are responsible for the functions of septate junction in epithelial cells. These discoveries encourage more studies on novel post-transcriptional regulation mechanisms. </p>","PeriodicalId":35444,"journal":{"name":"International Journal of Bioinformatics Research and Applications","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2014-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://sci-hub-pdf.com/10.1504/IJBRA.2014.062996","citationCount":"1","resultStr":"{\"title\":\"Discovering non-coding RNA elements in Drosophila 3' untranslated regions.\",\"authors\":\"Cuncong Zhong, Justen Andrews, Shaojie Zhang\",\"doi\":\"10.1504/IJBRA.2014.062996\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The Non-Coding RNA (ncRNA) elements in the 3' Untranslated Regions (3'-UTRs) are known to participate in the genes' post-transcriptional regulations. Inferring co-expression patterns of the genes through clustering these 3'-UTR ncRNA elements will provide invaluable insights for studying their biological functions. In this paper, we propose an improved RNA structural clustering pipeline. Benchmark of the new pipeline on Rfam data demonstrates over 10% performance improvements compared to the traditional hierarchical clustering pipeline. By applying the new clustering pipeline to 3'-UTRs of Drosophila melanogaster's genome, we have successfully identified 184 ncRNA clusters with 91.3% accuracy. One of these clusters corresponds to genes that are preferentially expressed in male Drosophila. Another cluster contains genes that are responsible for the functions of septate junction in epithelial cells. These discoveries encourage more studies on novel post-transcriptional regulation mechanisms. </p>\",\"PeriodicalId\":35444,\"journal\":{\"name\":\"International Journal of Bioinformatics Research and Applications\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2014-01-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://sci-hub-pdf.com/10.1504/IJBRA.2014.062996\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International Journal of Bioinformatics Research and Applications\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1504/IJBRA.2014.062996\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Health Professions\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Journal of Bioinformatics Research and Applications","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1504/IJBRA.2014.062996","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Health Professions","Score":null,"Total":0}
Discovering non-coding RNA elements in Drosophila 3' untranslated regions.
The Non-Coding RNA (ncRNA) elements in the 3' Untranslated Regions (3'-UTRs) are known to participate in the genes' post-transcriptional regulations. Inferring co-expression patterns of the genes through clustering these 3'-UTR ncRNA elements will provide invaluable insights for studying their biological functions. In this paper, we propose an improved RNA structural clustering pipeline. Benchmark of the new pipeline on Rfam data demonstrates over 10% performance improvements compared to the traditional hierarchical clustering pipeline. By applying the new clustering pipeline to 3'-UTRs of Drosophila melanogaster's genome, we have successfully identified 184 ncRNA clusters with 91.3% accuracy. One of these clusters corresponds to genes that are preferentially expressed in male Drosophila. Another cluster contains genes that are responsible for the functions of septate junction in epithelial cells. These discoveries encourage more studies on novel post-transcriptional regulation mechanisms.
期刊介绍:
Bioinformatics is an interdisciplinary research field that combines biology, computer science, mathematics and statistics into a broad-based field that will have profound impacts on all fields of biology. The emphasis of IJBRA is on basic bioinformatics research methods, tool development, performance evaluation and their applications in biology. IJBRA addresses the most innovative developments, research issues and solutions in bioinformatics and computational biology and their applications. Topics covered include Databases, bio-grid, system biology Biomedical image processing, modelling and simulation Bio-ontology and data mining, DNA assembly, clustering, mapping Computational genomics/proteomics Silico technology: computational intelligence, high performance computing E-health, telemedicine Gene expression, microarrays, identification, annotation Genetic algorithms, fuzzy logic, neural networks, data visualisation Hidden Markov models, machine learning, support vector machines Molecular evolution, phylogeny, modelling, simulation, sequence analysis Parallel algorithms/architectures, computational structural biology Phylogeny reconstruction algorithms, physiome, protein structure prediction Sequence assembly, search, alignment Signalling/computational biomedical data engineering Simulated annealing, statistical analysis, stochastic grammars.