ReviewCurrent opinion in genetics & development2014
Collection, integration and analysis of cancer genomic profiles: from data to insight.
Review in Current opinion in genetics & development, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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
12 citing papers in PubMed.
- Unveiling Disparities: Analyzing Hispanic Inclusion in Liver Cancer Research Databases in the United States.Journal of racial and ethnic health disparities · 2025Article
- Differential expression profiling of onco and tumor-suppressor genes from major-signaling pathways in Wilms' tumor.Pediatric surgery international · 2022Article
- Brief introduction of medical database and data mining technology in big data era.Journal of evidence-based medicine · 2020Review
- Misactivation of Hedgehog signaling causes inherited and sporadic cancers.The Journal of clinical investigation · 2019Review
- Identification of CTRP1 as a Prognostic Biomarker and Oncogene in Human Glioblastoma.BioMed research international · 2019Article
- Article
- Sirt3 enhances glioma cell viability by stabilizing Ku70-BAX interaction.OncoTargets and therapy · 2018Article
- Clinicopathological analysis of HOXD4 expression in diffuse gliomas and its correlation withOncotarget · 2017Article
- Morphological characterization of colorectal cancers in The Cancer Genome Atlas reveals distinct morphology-molecular associations: clinical and biological implications.Modern pathology : an official journal of the United States and Canadian Academy of Pathology, Inc · 2017Article
- RNA-guided CRISPR-Cas technologies for genome-scale investigation of disease processes.Journal of hematology & oncology · 2015Review
- Identification of Gene Expression Pattern Related to Breast Cancer Survival Using Integrated TCGA Datasets and Genomic Tools.BioMed research international · 2015Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors.
Funding
Abstract
The recent deluge of cancer genomics data provides a tremendous opportunity for the discovery of detailed mechanisms of tumorigenesis and the development of therapeutics. However, identifying the functionally relevant genomic alterations ('drivers') among the many non-oncogenic events ('passengers') presents a major challenge. Several new methods have been developed over the past few years that identify recurrently altered genes. Mapping the recurrent genomic alterations, such as somatic mutations and focal DNA copy-number alterations, onto individual tumor samples as tumor-specific event calls facilitates the identification of altered processes and pathways. The resulting reduction in complexity makes cancer genomics data more easily interpretable by cancer researchers and is now driving the development of powerful yet intuitive web-based analysis tools.
Indexed as
Identifiers
What OpenQuestion holds
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.