Baum_et_al_2019_Supplementary_Figures.pdf: Supplementary Figures S1 and S2. Legends are included under each figure. sbm-for-correlation-based-networks-master.zip: Archived source code of R and Python functions for the analyses and example workflow description at time of publication. Files are maintained at https://gitlab.com/biomodlih/sbm-for-correlation-based-networks and https://gitlab.com/kabaum/sbm-for-correlation-based-networks
Correlation networks are frequently used to statistically extract biological interactions between om...
Correlation networks are emerging as a powerful tool for modeling temporal mechanisms within the cel...
Correlation networks are ideal to describe the relationship between the expression profiles of genes...
Baum_et_al_2019_Supplementary_Figures.pdf: Supplementary Figures S1 and S2. Legends are included und...
AbstractObjectiveModelling the associations from high-throughput experimental molecular data has pro...
Background: Correlation network analysis has become an integral tool to study metabolite datasets. N...
<div><p>Building prediction models based on complex omics datasets such as transcriptomics, proteomi...
Abstract Background The models in this article generalize current models for both correlation networ...
BACKGROUND: Many aspects of biological functions can be modeled by biological networks, such as prot...
<p>Correlation networks based on 16S rRNA gene survey data collected as part of the Human Microbiome...
Network inference approaches are now widely used in biological applications to probe regulatory rela...
Biological networks play a paramount role in our understanding of complex biological phenomena, and ...
Many recent developments in network analysis have focused on multilayer networks, which one can use ...
Correlation networks are frequently used to statistically extract biological interactions between om...
The rise of network data in many different domains has offered researchers new insight into the prob...
Correlation networks are frequently used to statistically extract biological interactions between om...
Correlation networks are emerging as a powerful tool for modeling temporal mechanisms within the cel...
Correlation networks are ideal to describe the relationship between the expression profiles of genes...
Baum_et_al_2019_Supplementary_Figures.pdf: Supplementary Figures S1 and S2. Legends are included und...
AbstractObjectiveModelling the associations from high-throughput experimental molecular data has pro...
Background: Correlation network analysis has become an integral tool to study metabolite datasets. N...
<div><p>Building prediction models based on complex omics datasets such as transcriptomics, proteomi...
Abstract Background The models in this article generalize current models for both correlation networ...
BACKGROUND: Many aspects of biological functions can be modeled by biological networks, such as prot...
<p>Correlation networks based on 16S rRNA gene survey data collected as part of the Human Microbiome...
Network inference approaches are now widely used in biological applications to probe regulatory rela...
Biological networks play a paramount role in our understanding of complex biological phenomena, and ...
Many recent developments in network analysis have focused on multilayer networks, which one can use ...
Correlation networks are frequently used to statistically extract biological interactions between om...
The rise of network data in many different domains has offered researchers new insight into the prob...
Correlation networks are frequently used to statistically extract biological interactions between om...
Correlation networks are emerging as a powerful tool for modeling temporal mechanisms within the cel...
Correlation networks are ideal to describe the relationship between the expression profiles of genes...