Updated review of advances in microRNAs and complex diseases: towards systematic evaluation of computational models

Currently, there exist no generally accepted strategies of evaluating computational models for microRNA-disease associations (MDAs). Though K-fold cross validations and case studies seem to be must-have procedures, the value of K, the evaluation metrics, and the choice of query diseases as well as t...

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Bibliographic Details
Published inBriefings in bioinformatics Vol. 23; no. 6
Main Authors Huang, Li, Zhang, Li, Chen, Xing
Format Journal Article
LanguageEnglish
Published England 19.11.2022
Subjects
Algorithms
Computational Biology - methods
Computer Simulation
MicroRNAs - genetics
computational model
performance evaluation
association prediction
microRNA
complex diseases
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Summary:Currently, there exist no generally accepted strategies of evaluating computational models for microRNA-disease associations (MDAs). Though K-fold cross validations and case studies seem to be must-have procedures, the value of K, the evaluation metrics, and the choice of query diseases as well as the inclusion of other procedures (such as parameter sensitivity tests, ablation studies and computational cost reports) are all determined on a case-by-case basis and depending on the researchers’ choices. In the current review, we include a comprehensive analysis on how 29 state-of-the-art models for predicting MDAs were evaluated. Based on the analytical results, we recommend a feasible evaluation workflow that would suit any future model to facilitate fair and systematic assessment of predictive performance.
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ISSN:1467-5463
1477-4054
1477-4054
DOI:10.1093/bib/bbac407