This file contains the data that was used in the paper titled "A Flexible, Interpretable, and Accurate Approach for Imputing the Expression of Unmeasured Genes", which is submitted for review. The preprint is available at https://www.biorxiv.org/content/10.1101/2020.03.30.016675v1.abstrac
Abstract: Gene expression microarrays have rapidly become a standard experimental tool in the modern...
When dealing with large scale gene expression studies, observations are commonly contaminated by sou...
This article proposes nonparametric inference procedures for analyzing microarray gene expression da...
This file contains the data that was used in the paper titled "A Flexible, Interpretable, and Accura...
Classification based upon gene expression data: bias and precision of error rate
The purpose of this upload is to release the tissue-specific gene expression imputation models we ge...
Gene expression microarrays are now established as a standard tool in biological and biochemical lab...
This file contains the data that was used in the paper titled "Supervised-learning is an accurate me...
Imports graphics Description Non-parametric method for identifying differentially expressed (up- or ...
Summary. Microarray technology has become widespread as a means to investigate gene function and met...
In gene expression studies, missing values are a common problem with important consequences for the ...
Modern next-generation sequencing and microarray-based assays have empowered the computational biolo...
The purpose of this upload is to release the tissue-specific gene expression imputation models we ge...
Microarrays measure expression patterns of thousands of genes at a time, under same or diverse condi...
It has unambiguously been shown that genetic, environmental, demographic, and technical factors may ...
Abstract: Gene expression microarrays have rapidly become a standard experimental tool in the modern...
When dealing with large scale gene expression studies, observations are commonly contaminated by sou...
This article proposes nonparametric inference procedures for analyzing microarray gene expression da...
This file contains the data that was used in the paper titled "A Flexible, Interpretable, and Accura...
Classification based upon gene expression data: bias and precision of error rate
The purpose of this upload is to release the tissue-specific gene expression imputation models we ge...
Gene expression microarrays are now established as a standard tool in biological and biochemical lab...
This file contains the data that was used in the paper titled "Supervised-learning is an accurate me...
Imports graphics Description Non-parametric method for identifying differentially expressed (up- or ...
Summary. Microarray technology has become widespread as a means to investigate gene function and met...
In gene expression studies, missing values are a common problem with important consequences for the ...
Modern next-generation sequencing and microarray-based assays have empowered the computational biolo...
The purpose of this upload is to release the tissue-specific gene expression imputation models we ge...
Microarrays measure expression patterns of thousands of genes at a time, under same or diverse condi...
It has unambiguously been shown that genetic, environmental, demographic, and technical factors may ...
Abstract: Gene expression microarrays have rapidly become a standard experimental tool in the modern...
When dealing with large scale gene expression studies, observations are commonly contaminated by sou...
This article proposes nonparametric inference procedures for analyzing microarray gene expression da...