We are analyzing https://link.springer.com/article/10.1186/s12864-018-4528-x.

Title:
A systematic approach to RNA-associated motif discovery | BMC Genomics
Description:
Background Sequencing-based large screening of RNA-protein and RNA-RNA interactions has enabled the mechanistic study of post-transcriptional RNA processing and sorting, including exosome-mediated RNA secretion. The downstream analysis of RNA binding sites has encouraged the investigation of novel sequence motifs, which resulted in exceptional new challenges for identifying motifs from very short sequences (e.g., small non-coding RNAs or truncated messenger RNAs), where conventional methods tend to be ineffective. To address these challenges, we propose a novel motif-finding method and validate it on a wide range of RNA applications. Results We first perform motif analysis on microRNAs and longer RNA fragments from various cellular and exosomal sources, and then validate our prediction through literature search and experimental test. For example, a 4 bp-long motif, GUUG, was detected to be responsible for microRNA loading in exosomes involved in human colon cancer (SW620). Additional performance comparisons in various case studies have shown that this new approach outperforms several existing state-of-the-art methods in detecting motifs with exceptional high coverage and explicitness. Conclusions In this work, we have demonstrated the promising performance of a new motif discovery approach that is particularly effective in current RNA applications. Important discoveries resulting from this work include the identification of possible RNA-loading motifs in a variety of exosomes, as well as novel insights in sequence features of RNA cargos, i.e., short non-coding RNAs and messenger RNAs may share similar loading mechanism into exosomes. This method has been implemented and deployed as a new webserver named MDS2 which is accessible at http://sbbi-panda.unl.edu/MDS2/ , along with a standalone package available for download at https://github.com/sbbi/MDS2 .
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Keywords {🔍}

motifs, motif, exosomal, sequences, rna, mirna, internet, mirnas, article, input, mds, cell, binding, predicted, data, fig, sequence, short, google, scholar, exosomes, coverage, sites, cas, pvalue, study, rnas, finding, analysis, search, full, human, based, detection, adjusted, prediction, cited, background, bps, datasets, size, graph, mer, information, methods, method, similar, cells, significance, kmers,

Topics {✒️}

dbfrom=pubmed&id=23464877&retmode=ref&cmd=prlinks%5cnpapers2 /data-mining-practical-techniques-management/dp/0123748569 vens [gau][gua][gau][cag][ua][gc] /science/article/pii/s167202291500011x ohshima ///users/calixto/papers2/articles/2013/orenstein/ 7056&rep=rep1&type=pdf%5cnhttp jiang shu & juan cui hsa-mir-92a-3p micro−/nano-based devices nz/~ml/weka/book aligning protein multiple-alignments require consecutive base-pairing full size image identify cis-regulatory elements photoactivatable ribonucleoside-enhanced crosslinking single-stranded dna applications mycobacterium tuberculosis-infected cells adipocyte-derived exosomal mirnas gov/entrez/eutils/elink cis-regulatory binding sites rna-binding protein syncrip high-quality negative data top-ranked motif [agu] equal-size sampled datasets weighted motif-similarity graph large-scale random sampling tf-binding dna motif directed di-mer graph protein-binding microarray data bmc genomics [internet] high-throughput sequencing technologies recently-released sequencing data open-access database ago2-par-clip data rna-rna interaction sites initial di-mer graph gov/pubmed/23622248 kheradpour gov/pubmed/28423355%0ahttp gov/pubmed/21679436 keerthikumar gov/pubmed/25388151 kalra gov/pubmed/21543443 pietrokovski nucleic acids res /nar/article/doi/10 article download pdf k-mer similarity graph mirna-mrna interaction sites human mirna-mrna interaction top-ranked predicted motif cell-specific packaging mechanisms exosome-mediated intercellular communication

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WebPage:
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         description:Sequencing-based large screening of RNA-protein and RNA-RNA interactions has enabled the mechanistic study of post-transcriptional RNA processing and sorting, including exosome-mediated RNA secretion. The downstream analysis of RNA binding sites has encouraged the investigation of novel sequence motifs, which resulted in exceptional new challenges for identifying motifs from very short sequences (e.g., small non-coding RNAs or truncated messenger RNAs), where conventional methods tend to be ineffective. To address these challenges, we propose a novel motif-finding method and validate it on a wide range of RNA applications. We first perform motif analysis on microRNAs and longer RNA fragments from various cellular and exosomal sources, and then validate our prediction through literature search and experimental test. For example, a 4 bp-long motif, GUUG, was detected to be responsible for microRNA loading in exosomes involved in human colon cancer (SW620). Additional performance comparisons in various case studies have shown that this new approach outperforms several existing state-of-the-art methods in detecting motifs with exceptional high coverage and explicitness. In this work, we have demonstrated the promising performance of a new motif discovery approach that is particularly effective in current RNA applications. Important discoveries resulting from this work include the identification of possible RNA-loading motifs in a variety of exosomes, as well as novel insights in sequence features of RNA cargos, i.e., short non-coding RNAs and messenger RNAs may share similar loading mechanism into exosomes. This method has been implemented and deployed as a new webserver named MDS2 which is accessible at http://sbbi-panda.unl.edu/MDS2/ , along with a standalone package available for download at https://github.com/sbbi/MDS2 .
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         general
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         Proteomics
         Animal Genetics and Genomics
         Microbial Genetics and Genomics
         Plant Genetics and Genomics
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