Predicting Viral Infection From High-Dimensional Biomarker Trajectories.
about
Gene expression-based classifiers identify Staphylococcus aureus infection in mice and humansWhat 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
P2860
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P2860
Predicting Viral Infection From High-Dimensional Biomarker Trajectories.
description
2011 nî lūn-bûn
@nan
2011年の論文
@ja
2011年論文
@yue
2011年論文
@zh-hant
2011年論文
@zh-hk
2011年論文
@zh-mo
2011年論文
@zh-tw
2011年论文
@wuu
2011年论文
@zh
2011年论文
@zh-cn
name
Predicting Viral Infection From High-Dimensional Biomarker Trajectories.
@en
type
label
Predicting Viral Infection From High-Dimensional Biomarker Trajectories.
@en
prefLabel
Predicting Viral Infection From High-Dimensional Biomarker Trajectories.
@en
P2093
P2860
P1476
Predicting Viral Infection From High-Dimensional Biomarker Trajectories.
@en
P2093
Aimee Zaas
Christopher Woods
David Dunson
Geoffrey S Ginsburg
Joseph Lucas
Minhua Chen
P2860
P304
P356
10.1198/JASA.2011.AP10611
P407
P577
2011-01-01T00:00:00Z