Matches in SemOpenAlex for { <https://semopenalex.org/work/W2100097984> ?p ?o ?g. }
Showing items 1 to 100 of
100
with 100 items per page.
- W2100097984 endingPage "215" @default.
- W2100097984 startingPage "209" @default.
- W2100097984 abstract "Modern molecular technologies allow the collection of large amounts of high-throughput data on the functional attributes of genes. Often multiple technologies and study designs are used to address the same biological question such as which genes are overexpressed in a specific disease state. Consequently, there is considerable interest in methods that can integrate across datasets to present a unified set of predictions.An important aspect of data integration is being able to account for the fact that datasets may differ in how accurately they capture the biological signal of interest. While many methods to address this problem exist, they always rely either on dataset internal statistics, which reflect data structure and not necessarily biological relevance, or external gold standards, which may not always be available. We present a new rank aggregation method for data integration that requires neither external standards nor internal statistics but relies on Bayesian reasoning to assess dataset relevance. We demonstrate that our method outperforms established techniques and significantly improves the predictive power of rank-based aggregations. We show that our method, which does not require an external gold standard, provides reliable estimates of dataset relevance and allows the same set of data to be integrated differently depending on the specific signal of interest.The method is implemented in R and is freely available at http://www.pitt.edu/~mchikina/BIRRA/.Supplementary data are available at Bioinformatics online." @default.
- W2100097984 created "2016-06-24" @default.
- W2100097984 creator A5032864572 @default.
- W2100097984 creator A5034705320 @default.
- W2100097984 creator A5058017696 @default.
- W2100097984 date "2014-09-29" @default.
- W2100097984 modified "2023-09-25" @default.
- W2100097984 title "Hybrid Bayesian-rank integration approach improves the predictive power of genomic dataset aggregation" @default.
- W2100097984 cites W1976386441 @default.
- W2100097984 cites W1988294855 @default.
- W2100097984 cites W1998712640 @default.
- W2100097984 cites W2006594553 @default.
- W2100097984 cites W2020541351 @default.
- W2100097984 cites W2029276959 @default.
- W2100097984 cites W2046618236 @default.
- W2100097984 cites W2095956310 @default.
- W2100097984 cites W2132960606 @default.
- W2100097984 cites W2134128560 @default.
- W2100097984 cites W2135338058 @default.
- W2100097984 cites W2146511318 @default.
- W2100097984 cites W2156925439 @default.
- W2100097984 cites W2158240093 @default.
- W2100097984 cites W2162142896 @default.
- W2100097984 doi "https://doi.org/10.1093/bioinformatics/btu518" @default.
- W2100097984 hasPubMedCentralId "https://www.ncbi.nlm.nih.gov/pmc/articles/4287939" @default.
- W2100097984 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/25266226" @default.
- W2100097984 hasPublicationYear "2014" @default.
- W2100097984 type Work @default.
- W2100097984 sameAs 2100097984 @default.
- W2100097984 citedByCount "15" @default.
- W2100097984 countsByYear W21000979842015 @default.
- W2100097984 countsByYear W21000979842016 @default.
- W2100097984 countsByYear W21000979842017 @default.
- W2100097984 countsByYear W21000979842018 @default.
- W2100097984 countsByYear W21000979842019 @default.
- W2100097984 countsByYear W21000979842022 @default.
- W2100097984 countsByYear W21000979842023 @default.
- W2100097984 crossrefType "journal-article" @default.
- W2100097984 hasAuthorship W2100097984A5032864572 @default.
- W2100097984 hasAuthorship W2100097984A5034705320 @default.
- W2100097984 hasAuthorship W2100097984A5058017696 @default.
- W2100097984 hasBestOaLocation W21000979841 @default.
- W2100097984 hasConcept C105795698 @default.
- W2100097984 hasConcept C107673813 @default.
- W2100097984 hasConcept C114614502 @default.
- W2100097984 hasConcept C119857082 @default.
- W2100097984 hasConcept C124101348 @default.
- W2100097984 hasConcept C154945302 @default.
- W2100097984 hasConcept C158154518 @default.
- W2100097984 hasConcept C164226766 @default.
- W2100097984 hasConcept C177264268 @default.
- W2100097984 hasConcept C17744445 @default.
- W2100097984 hasConcept C199360897 @default.
- W2100097984 hasConcept C199539241 @default.
- W2100097984 hasConcept C33923547 @default.
- W2100097984 hasConcept C41008148 @default.
- W2100097984 hasConcept C58489278 @default.
- W2100097984 hasConcept C72634772 @default.
- W2100097984 hasConcept C96608239 @default.
- W2100097984 hasConceptScore W2100097984C105795698 @default.
- W2100097984 hasConceptScore W2100097984C107673813 @default.
- W2100097984 hasConceptScore W2100097984C114614502 @default.
- W2100097984 hasConceptScore W2100097984C119857082 @default.
- W2100097984 hasConceptScore W2100097984C124101348 @default.
- W2100097984 hasConceptScore W2100097984C154945302 @default.
- W2100097984 hasConceptScore W2100097984C158154518 @default.
- W2100097984 hasConceptScore W2100097984C164226766 @default.
- W2100097984 hasConceptScore W2100097984C177264268 @default.
- W2100097984 hasConceptScore W2100097984C17744445 @default.
- W2100097984 hasConceptScore W2100097984C199360897 @default.
- W2100097984 hasConceptScore W2100097984C199539241 @default.
- W2100097984 hasConceptScore W2100097984C33923547 @default.
- W2100097984 hasConceptScore W2100097984C41008148 @default.
- W2100097984 hasConceptScore W2100097984C58489278 @default.
- W2100097984 hasConceptScore W2100097984C72634772 @default.
- W2100097984 hasConceptScore W2100097984C96608239 @default.
- W2100097984 hasIssue "2" @default.
- W2100097984 hasLocation W21000979841 @default.
- W2100097984 hasLocation W21000979842 @default.
- W2100097984 hasLocation W21000979843 @default.
- W2100097984 hasLocation W21000979844 @default.
- W2100097984 hasOpenAccess W2100097984 @default.
- W2100097984 hasPrimaryLocation W21000979841 @default.
- W2100097984 hasRelatedWork W1543345676 @default.
- W2100097984 hasRelatedWork W2078736197 @default.
- W2100097984 hasRelatedWork W2091018730 @default.
- W2100097984 hasRelatedWork W2098669189 @default.
- W2100097984 hasRelatedWork W2250140425 @default.
- W2100097984 hasRelatedWork W2389064843 @default.
- W2100097984 hasRelatedWork W2389272265 @default.
- W2100097984 hasRelatedWork W2734587838 @default.
- W2100097984 hasRelatedWork W4293721826 @default.
- W2100097984 hasRelatedWork W4377238720 @default.
- W2100097984 hasVolume "31" @default.
- W2100097984 isParatext "false" @default.
- W2100097984 isRetracted "false" @default.
- W2100097984 magId "2100097984" @default.
- W2100097984 workType "article" @default.