Predicting Viral Infection From High-Dimensional Biomarker Trajectories. - Wikidata - wikimedia - TriplyDB

Predicting Viral Infection From High-Dimensional Biomarker Trajectories.

Predicting Viral Infection From High-Dimensional Biomarker Trajectories.

http://www.wikidata.org/entity/Q36862045

about

Gene expression-based classifiers identify Staphylococcus aureus infection in mice and humans What was old is new again: using the host response to diagnose infectious disease.Bayesian joint analysis of heterogeneous genomics data.High-Dimensional Longitudinal Genomic Data: An analysis used for monitoring viral infections.Minimum redundancy maximum relevance feature selection approach for temporal gene expression data.Time-variant clustering model for understanding cell fate decisions.Bayesian Exploratory Factor Analysis.Mining geographic variations of Plasmodium vivax for active surveillance: a case study in China.Shared kernel Bayesian screening.Do Biology Students Really Hate Math? Empirical Insights into Undergraduate Life Science Majors' Emotions about Mathematics.Dynamic transcriptional signatures and network responses for clinical symptoms in influenza-infected human subjects using systems biology approaches.A crowdsourced analysis to identify ab initio molecular signatures predictive of susceptibility to viral infection

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Predicting Viral Infection From High-Dimensional Biomarker Trajectories.

http://www.wikidata.org/entity/Q36862045

description

2011 nî lūn-bûn

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Predicting Viral Infection From High-Dimensional Biomarker Trajectories.

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Predicting Viral Infection From High-Dimensional Biomarker Trajectories.

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JASA.2011.AP10611

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Journal of the American Statistical Association

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Predicting Viral Infection From High-Dimensional Biomarker Trajectories.

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Aimee Zaas

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Christopher Woods

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David Dunson

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Geoffrey S Ginsburg

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Joseph Lucas

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Minhua Chen

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P2860

The DNA sequence of the human X chromosome

Gender-specific gene expression in post-mortem human brain: localization to sex chromosomes

Bioinformatics enrichment tools: paths toward the comprehensive functional analysis of large gene lists

MAVS and MyD88 are essential for innate immunity but not cytotoxic T lymphocyte response against respiratory syncytial virus

Significance analysis of time course microarray experiments.

Gene expression signatures diagnose influenza and other symptomatic respiratory viral infections in humans

Dynamic modeling of gene expression data.

Bayesian modeling of incidence and progression of disease from cross-sectional data.

Clustering of time-course gene expression data using a mixed-effects model with B-splines.

Continuous representations of time-series gene expression data.

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1259-1279

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10.1198/JASA.2011.AP10611

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106

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