Optimal Bayesian Filtering for Biomarker Discovery: Performance and Robustness

Optimal Bayesian feature filtering (OBF) is a fast and memory-efficient algorithm that optimally identifies markers with distributional differences between treatment groups under Gaussian models. Here, we study the performance and robustness of OBF for biomarker discovery. Our contributions are twof...

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Veröffentlicht in:	IEEE/ACM transactions on computational biology and bioinformatics 2020-01, Vol.17 (1), p.250-263
Hauptverfasser:	Foroughi pour, Ali, Dalton, Lori A.
Format:	Artikel
Sprache:	eng
Schlagworte:	Acute myeloid leukemia Algorithms Bayes methods Bayes Theorem Bayesian analysis Bayesian modeling Bayesian variable selection Bioinformatics Biological system modeling biomarker discovery Biomarkers Colon Colon cancer Computational Biology - methods Computational modeling Computer applications Computer simulation Data models Databases, Factual Feature extraction feature selection Filtration Humans Leukemia Mathematical models Myeloid leukemia Neoplasms - diagnosis Neoplasms - metabolism Optimization Parameter robustness Robustness
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