Search results for " Hypergeometric distribution"

showing 3 items of 3 documents

Prediction of Disease–lncRNA Associations via Machine Learning and Big Data Approaches

2021

This chapter introduces long non-coding RNAs and their role in the occurrence and progress of diseases. The discovery of novel lncRNA-disease associations may provide valuable input to the understanding of disease mechanisms at the lncRNA level, as well as to the detection of biomarkers for disease diagnosis, treatment, prognosis, and prevention. Unfortunately, due to costs and time complexity, the number of possible disease-related lncRNAs verified by traditional biological experiments is very limited. Computational approaches for the prediction of potential disease-lncRNA associations can effectively decrease the time and cost of biological experiments. We first review the main computatio…

business.industryComputer scienceBig Data Technologies Biological Processes Computational Approaches Disease–lncRNA Associations Non-Coding RNA Hypergeometric distribution Leave One Out Cross Validation Long non-coding RNA Master-Slave Architecture Micro-RNA.Big dataArtificial intelligenceDiseasebusinessMachine learningcomputer.software_genrecomputer
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COVARIANCE AND CORRELATION ESTIMATORS IN BIPARTITE SYSTEMS

2017

We present a weighted estimator of the covariance and correlation in bipartite complex systems with a double layer of heterogeneity. The advantage provided by the weighted estimators lies in the fact that the unweighted sample covariance and correlation can be shown to possess a bias. Indeed, such a bias affects real bipartite systems, and, for example, we report its effects on two empirical systems, one social and the other biological. On the contrary, our newly proposed weighted estimators remove the bias and are better suited to describe such systems.

Bipartite systemsBiological systemsWallenius non-central Hypergeometric DistributionCorrelation AnalysisComplex SystemsSocial systemsSettore FIS/07 - Fisica Applicata(Beni Culturali Ambientali Biol.e Medicin)
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Objective Priors for Discrete Parameter Spaces

2012

This article considers the development of objective prior distributions for discrete parameter spaces. Formal approaches to such development—such as the reference prior approach—often result in a constant prior for a discrete parameter, which is questionable for problems that exhibit certain types of structure. To take advantage of structure, this article proposes embedding the original problem in a continuous problem that preserves the structure, and then using standard reference prior theory to determine the appropriate objective prior. Four different possibilities for this embedding are explored, and applied to a population-size model, the hypergeometric distribution, the multivariate hy…

Statistics and ProbabilityMathematical optimizationNegative hypergeometric distributionGeometric distributionHypergeometric distributionDirichlet distributionBinomial distributionsymbols.namesakeBeta-binomial distributionPrior probabilitysymbolsStatistics Probability and UncertaintyCompound probability distributionMathematicsJournal of the American Statistical Association
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