ReviewBriefings in bioinformatics2013
Cancer gene prioritization by integrative analysis of mRNA expression and DNA copy number data: a comparative review.
Review in Briefings in bioinformatics, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 papers, 2 of them syntheses that pooled it.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
23 citing papers in PubMed, 2 syntheses or guidelines pooled it.
- Pooled it
- A meta-analysis of multiple matched copy number and transcriptomics data sets for inferring gene regulatory relationships.PloS one · 2014Pooled it
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- Role of Artificial Intelligence in Drug Discovery and Target Identification in Cancer.Current drug delivery · 2024Review
- CiberAMP: AnBiology · 2022Article
- Article
- Set-Wise Differential Interaction Between Copy Number Alterations and Gene Expressions of Lower-Grade Glioma Reveals Prognosis-Associated Pathways.Entropy (Basel, Switzerland) · 2020Article
- A comparative study of multi-omics integration tools for cancer driver gene identification and tumour subtyping.Briefings in bioinformatics · 2020Article
- MVisAGe Identifies Concordant and Discordant Genomic Alterations of Driver Genes in Squamous Tumors.Cancer research · 2018Article
- The Integrative Method Based on the Module-Network for Identifying Driver Genes in Cancer Subtypes.Molecules (Basel, Switzerland) · 2018Article
- Sparse multivariate factor analysis regression models and its applications to integrative genomics analysis.Genetic epidemiology · 2017Article
- FocalScan: Scanning for altered genes in cancer based on coordinated DNA and RNA change.Nucleic acids research · 2016Article
- Identifying candidate drivers of drug response in heterogeneous cancer by mining high throughput genomics data.BMC genomics · 2016Article
- Investigating inter-chromosomal regulatory relationships through a comprehensive meta-analysis of matched copy number and transcriptomics data sets.BMC genomics · 2015Article
- Integrating genetics and epigenetics in breast cancer: biological insights, experimental, computational methods and therapeutic potential.BMC systems biology · 2015Review
- An integrated approach to reveal miRNAs' impacts on the functional consequence of copy number alterations in cancer.Scientific reports · 2015Article
- Integrated exon level expression analysis of driver genes explain their role in colorectal cancer.PloS one · 2014Article
- Article
- Text mining in cancer gene and pathway prioritization.Cancer informatics · 2014Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
A variety of genome-wide profiling techniques are available to investigate complementary aspects of genome structure and function. Integrative analysis of heterogeneous data sources can reveal higher level interactions that cannot be detected based on individual observations. A standard integration task in cancer studies is to identify altered genomic regions that induce changes in the expression of the associated genes based on joint analysis of genome-wide gene expression and copy number profiling measurements. In this review, we highlight common approaches to genomic data integration and provide a transparent benchmarking procedure to quantitatively compare method performances in cancer gene prioritization. Algorithms, data sets and benchmarking results are available at http://intcomp.r-forge.r-project.org.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.