About: RPiRLS: Quantitative Predictions of RNA Interacting with Any Protein of Known Sequence

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An Entity of Type : schema:ScholarlyArticle, within Data Space : wasabi.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
has title	RPiRLS: Quantitative Predictions of RNA Interacting with Any Protein of Known Sequence
Creator	Chen, Danze Cui, Wenjuan Shen, Wen-Jun Xu, Jianzhen Zhang, Jieming
Source	PMC
abstract	RNA-protein interactions (RPIs) have critical roles in numerous fundamental biological processes, such as post-transcriptional gene regulation, viral assembly, cellular defence and protein synthesis. As the number of available RNA-protein binding experimental data has increased rapidly due to high-throughput sequencing methods, it is now possible to measure and understand RNA-protein interactions by computational methods. In this study, we integrate a sequence-based derived kernel with regularized least squares to perform prediction. The derived kernel exploits the contextual information around an amino acid or a nucleic acid as well as the repetitive conserved motif information. We propose a novel machine learning method, called RPiRLS to predict the interaction between any RNA and protein of known sequences. For the RPiRLS classifier, each protein sequence comprises up to 20 diverse amino acids but for the RPiRLS-7G classifier, each protein sequence is represented by using 7-letter reduced alphabets based on their physiochemical properties. We evaluated both methods on a number of benchmark data sets and compared their performances with two newly developed and state-of-the-art methods, RPI-Pred and IPMiner. On the non-redundant benchmark test sets extracted from the PRIDB, the RPiRLS method outperformed RPI-Pred and IPMiner in terms of accuracy, specificity and sensitivity. Further, RPiRLS achieved an accuracy of 92% on the prediction of lncRNA-protein interactions. The proposed method can also be extended to construct RNA-protein interaction networks. The RPiRLS web server is freely available at http://bmc.med.stu.edu.cn/RPiRLS.
has issue date	2018-02-28(xsd:dateTime)
bibo:doi	10.3390/molecules23030540
bibo:pmid	29495575
has license	cc-by
sha1sum (hex)	f595066c0454a407001920c8baf1edb260e9bb9d
schema:url	https://doi.org/10.3390/molecules23030540
resource representing a document's title	RPiRLS: Quantitative Predictions of RNA Interacting with Any Protein of Known Sequence
has PubMed Central identifier	PMC6017498
has PubMed identifier	29495575
schema:publication	Molecules
resource representing a document's body	covid:f595066c0454a407001920c8baf1edb260e9bb9d#body_text
is schema:about of	named entity 'PROTEIN SYNTHESIS' named entity 'PROTEIN SEQUENCE' named entity 'RAPIDLY' named entity 'CONSTRUCT' named entity 'STATE' named entity 'RNA' named entity 'NOVEL' named entity 'REDUNDANT' named entity 'REPETITIVE' named entity 'OF-' named entity 'DUE TO' named entity 'HTTP' named entity 'DATA SETS' named entity 'THEIR' named entity 'SEQUENCES' named entity 'INTERACTION' named entity 'STU' named entity 'INCREASED' named entity 'HIGH-THROUGHPUT SEQUENCING' named entity 'PERFORMANCES' named entity 'BASED' named entity 'AVAILABLE' named entity 'ALPHABETS' named entity 'INFORMATION' named entity 'LETTER' named entity 'RNA' named entity 'fundamental' named entity 'derived' named entity 'prediction' named entity 'CLASSIFIER' named entity 'MOTIF' named entity 'EXTRACTED' named entity 'PERFORM' named entity 'MED' named entity 'REDUCED' named entity 'STUDY' named entity 'ROLES' named entity 'EXPERIMENTAL DATA' named entity 'PROPERTIES' named entity 'POST-TRANSCRIPTIONAL GENE REGULATION' named entity 'BENCHMARK' named entity 'BIOLOGICAL PROCESSES' named entity 'PROTEIN INTERACTIONS' named entity 'COMPUTATIONAL' named entity 'SENSITIVITY' named entity 'BUT' named entity 'EVALUATED' named entity 'RPI' named entity 'EXPLOITS' named entity 'VIRAL ASSEMBLY' named entity 'AMINO ACID' named entity 'USING' named entity 'PREDICT' named entity 'KERNEL' named entity 'METHOD' named entity 'KNOWN' named entity 'CONSERVED' named entity 'NUMBER OF' named entity 'KNOWN' named entity 'RNA' named entity 'INTERACTING' named entity 'UNDERSTAND' named entity 'WEB SERVER' named entity 'HAVE' named entity 'PREDICTION' named entity 'POSSIBLE' named entity 'FREELY' named entity 'CRITICAL' named entity 'ACCURACY' named entity 'NEWLY' named entity 'AMINO ACIDS' named entity 'DIVERSE' named entity 'CELLULAR' named entity 'UP TO' named entity 'LEAST SQUARES' named entity 'TEST' named entity 'ART'

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