ArticleAdvancements in genetic engineering2012
Subtyping of Gliomaby Combining Gene Expression and CNVs Data Based on a Compressive Sensing Approach.
Article in Advancements in genetic engineering, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Sparse models for correlative and integrative analysis of imaging and genetic data.Journal of neuroscience methods · 2014Review
- Population clustering based on copy number variations detected from next generation sequencing data.Journal of bioinformatics and computational biology · 2014Article
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
It is realized that a combined analysis of different types of genomic measurements tends to give more reliable classification results. However, how to efficiently combine data with different resolutions is challenging. We propose a novel compressed sensing based approach for the combined analysis of gene expression and copy number variants data for the purpose of subtyping six types of Gliomas. Experimental results show that the proposed combined approach can substantially improve the classification accuracy compared to that of using either of individual data type. The proposed approach can be applicable to many other types of genomic data.
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Registered trials
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