FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W2793136329> ?p ?o ?g. }

• W2793136329 endingPage "3110" @default.
• W2793136329 startingPage "3101" @default.
• W2793136329 abstract "Abstract Motivation Long non-coding RNAs (lncRNAs) are defined as transcripts longer than 200 nt that do not get translated into proteins. Often these transcripts are processed (spliced, capped and polyadenylated) and some are known to have important biological functions. However, most lncRNAs have unknown or poorly understood functions. Nevertheless, because of their potential role in cancer, lncRNAs are receiving a lot of attention, and the need for computational tools to predict their possible mechanisms of action is more than ever. Fundamentally, most of the known lncRNA mechanisms involve RNA–RNA and/or RNA–protein interactions. Through accurate predictions of each kind of interaction and integration of these predictions, it is possible to elucidate potential mechanisms for a given lncRNA. Results Here, we introduce MechRNA, a pipeline for corroborating RNA–RNA interaction prediction and protein binding prediction for identifying possible lncRNA mechanisms involving specific targets or on a transcriptome-wide scale. The first stage uses a version of IntaRNA2 with added functionality for efficient prediction of RNA–RNA interactions with very long input sequences, allowing for large-scale analysis of lncRNA interactions with little or no loss of optimality. The second stage integrates protein binding information pre-computed by GraphProt, for both the lncRNA and the target. The final stage involves inferring the most likely mechanism for each lncRNA/target pair. This is achieved by generating candidate mechanisms from the predicted interactions, the relative locations of these interactions and correlation data, followed by selection of the most likely mechanistic explanation using a combined P-value. We applied MechRNA on a number of recently identified cancer-related lncRNAs (PCAT1, PCAT29 and ARLnc1) and also on two well-studied lncRNAs (PCA3 and 7SL). This led to the identification of hundreds of high confidence potential targets for each lncRNA and corresponding mechanisms. These predictions include the known competitive mechanism of 7SL with HuR for binding on the tumor suppressor TP53, as well as mechanisms expanding what is known about PCAT1 and ARLn1 and their targets BRCA2 and AR, respectively. For PCAT1-BRCA2, the mechanism involves competitive binding with HuR, which we confirmed using HuR immunoprecipitation assays. Availability and implementation MechRNA is available for download at https://bitbucket.org/compbio/mechrna. Supplementary information Supplementary data are available at Bioinformatics online." @default.
• W2793136329 created "2018-03-29" @default.
• W2793136329 creator A5003311852 @default.
• W2793136329 creator A5006028146 @default.
• W2793136329 creator A5015167428 @default.
• W2793136329 creator A5017672883 @default.
• W2793136329 creator A5020006331 @default.
• W2793136329 creator A5041266113 @default.
• W2793136329 creator A5042282214 @default.
• W2793136329 creator A5042505411 @default.
• W2793136329 creator A5048247983 @default.
• W2793136329 creator A5050325886 @default.
• W2793136329 creator A5083427841 @default.
• W2793136329 creator A5084563414 @default.
• W2793136329 date "2018-04-03" @default.
• W2793136329 modified "2023-09-26" @default.
• W2793136329 title "MechRNA: prediction of lncRNA mechanisms from RNA–RNA and RNA–protein interactions" @default.
• W2793136329 cites W1592870802 @default.
• W2793136329 cites W1963867859 @default.
• W2793136329 cites W1980914060 @default.
• W2793136329 cites W1983815263 @default.
• W2793136329 cites W1992114227 @default.
• W2793136329 cites W2003553455 @default.
• W2793136329 cites W2011977212 @default.
• W2793136329 cites W2014665031 @default.
• W2793136329 cites W2019381697 @default.
• W2793136329 cites W2029919331 @default.
• W2793136329 cites W2038438413 @default.
• W2793136329 cites W2043653977 @default.
• W2793136329 cites W2048709308 @default.
• W2793136329 cites W2053003053 @default.
• W2793136329 cites W2054630268 @default.
• W2793136329 cites W2059646461 @default.
• W2793136329 cites W2073858449 @default.
• W2793136329 cites W2086561953 @default.
• W2793136329 cites W2091356219 @default.
• W2793136329 cites W2094253263 @default.
• W2793136329 cites W2100893713 @default.
• W2793136329 cites W2103375140 @default.
• W2793136329 cites W2111471117 @default.
• W2793136329 cites W2111688179 @default.
• W2793136329 cites W2114532236 @default.
• W2793136329 cites W2116383371 @default.
• W2793136329 cites W2117994680 @default.
• W2793136329 cites W2119340328 @default.
• W2793136329 cites W2121352589 @default.
• W2793136329 cites W2129375421 @default.
• W2793136329 cites W2129706781 @default.
• W2793136329 cites W2131797752 @default.
• W2793136329 cites W2132081807 @default.
• W2793136329 cites W2132863465 @default.
• W2793136329 cites W2144723744 @default.
• W2793136329 cites W2145733907 @default.
• W2793136329 cites W2147900600 @default.
• W2793136329 cites W2158485828 @default.
• W2793136329 cites W2160515562 @default.
• W2793136329 cites W2161043701 @default.
• W2793136329 cites W2163489349 @default.
• W2793136329 cites W2165238410 @default.
• W2793136329 cites W2166268906 @default.
• W2793136329 cites W2166810745 @default.
• W2793136329 cites W2168619725 @default.
• W2793136329 cites W2169769858 @default.
• W2793136329 cites W2171809973 @default.
• W2793136329 cites W2177605184 @default.
• W2793136329 cites W2179438025 @default.
• W2793136329 cites W2239613263 @default.
• W2793136329 cites W2307041907 @default.
• W2793136329 cites W2339414115 @default.
• W2793136329 cites W2342788749 @default.
• W2793136329 cites W2491558565 @default.
• W2793136329 cites W2521409454 @default.
• W2793136329 cites W2524206229 @default.
• W2793136329 cites W2560425874 @default.
• W2793136329 cites W2577903052 @default.
• W2793136329 cites W2589484563 @default.
• W2793136329 cites W2610733803 @default.
• W2793136329 cites W2765241643 @default.
• W2793136329 cites W2802042505 @default.
• W2793136329 cites W2803499181 @default.
• W2793136329 doi "https://doi.org/10.1093/bioinformatics/bty208" @default.
• W2793136329 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/6137976" @default.
• W2793136329 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/29617966" @default.
• W2793136329 hasPublicationYear "2018" @default.
• W2793136329 type Work @default.
• W2793136329 sameAs 2793136329 @default.
• W2793136329 citedByCount "45" @default.
• W2793136329 countsByYear W27931363292018 @default.
• W2793136329 countsByYear W27931363292019 @default.
• W2793136329 countsByYear W27931363292020 @default.
• W2793136329 countsByYear W27931363292021 @default.
• W2793136329 countsByYear W27931363292022 @default.
• W2793136329 countsByYear W27931363292023 @default.
• W2793136329 crossrefType "journal-article" @default.
• W2793136329 hasAuthorship W2793136329A5003311852 @default.
• W2793136329 hasAuthorship W2793136329A5006028146 @default.
• W2793136329 hasAuthorship W2793136329A5015167428 @default.
• W2793136329 hasAuthorship W2793136329A5017672883 @default.

• next