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Integrating gene set analysis and nonlinear predictive modeling of disease phenotypes using a Bayesian multitask formulation
BACKGROUND: Identifying molecular signatures of disease phenotypes is studied using two mainstream approaches: (i) Predictive modeling methods such as linear classification and regression algorithms are used to find signatures predictive of phenotypes from genomic data, which may not be robust due t...
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| Pubblicato in: | BMC Bioinformatics |
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| Autore principale: | |
| Natura: | Artigo |
| Lingua: | Inglês |
| Pubblicazione: |
BioMed Central
2016
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| Soggetti: | |
| Accesso online: | https://ncbi.nlm.nih.gov/pmc/articles/PMC5249028/ https://ncbi.nlm.nih.gov/pubmed/28105911 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1186/s12859-016-1311-3 |
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