ReviewNature reviews. Genetics2014
Expanding the computational toolbox for mining cancer genomes.
Review in Nature reviews. Genetics, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 99 papers, 1 of them a synthesis that pooled it.
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
99 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Guidelines for cytogenetic investigations in tumours.European journal of human genetics : EJHG · 2016Guideline
- Cancer detection via one-shot learning: integrating gene expression and genomic mutation analysis.BMC bioinformatics · 2025Article
- Chromoanagenesis in Osteosarcoma.Biomolecules · 2025Review
- ECD-CDGI: An efficient energy-constrained diffusion model for cancer driver gene identification.PLoS computational biology · 2024Article
- Optimizing Design of Genomics Studies for Clonal Evolution Analysis.bioRxiv : the preprint server for biology · 2024Article
- Optimizing design of genomics studies for clonal evolution analysis.Bioinformatics advances · 2024Article
- The Cytotoxic Properties of Extreme Fungi's Bioactive Components-An Updated Metabolic and Omics Overview.Life (Basel, Switzerland) · 2023Review
- Article
- Pancan-MNVQTLdb: systematic identification of multi-nucleotide variant quantitative trait loci in 33 cancer types.NAR cancer · 2022Article
- Hepatobiliary Tumor Organoids Reveal HLA Class I Neoantigen Landscape and Antitumoral Activity of Neoantigen Peptide Enhanced with Immune Checkpoint Inhibitors.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2022Article
- Computational analysis of cancer genome sequencing data.Nature reviews. Genetics · 2022Review
- Fusion genes as biomarkers in pediatric cancers: A review of the current state and applicability in diagnostics and personalized therapy.Cancer letters · 2021Review
- Identifying and Targeting Human Tumor Antigens for T Cell-Based Immunotherapy of Solid Tumors.Cancer cell · 2020Review
- DNA and RNA sequencing identified a novel oncogene VPS35 in liver hepatocellular carcinoma.Oncogene · 2020Article
- QuaDMutNetEx: a method for detecting cancer driver genes with low mutation frequency.BMC bioinformatics · 2020Article
- A review on tumor heterogeneity and evolution in multiple myeloma: pathological, radiological, molecular genetics, and clinical integration.Virchows Archiv : an international journal of pathology · 2020Review
- The Use of Molecular Subtypes for Precision Therapy of Recurrent and Metastatic Gastrointestinal Stromal Tumor.OncoTargets and therapy · 2020Review
- Progress in Neoantigen Targeted Cancer Immunotherapies.Frontiers in cell and developmental biology · 2020Review
- Modulation of tumor microenvironment for immunotherapy: focus on nanomaterial-based strategies.Theranostics · 2020Review
- Next-generation computational tools for interrogating cancer immunity.Nature reviews. Genetics · 2019Review
39 more citing papers are in PubMed but not listed here.
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
High-throughput DNA sequencing has revolutionized the study of cancer genomics with numerous discoveries that are relevant to cancer diagnosis and treatment. The latest sequencing and analysis methods have successfully identified somatic alterations, including single-nucleotide variants, insertions and deletions, copy-number aberrations, structural variants and gene fusions. Additional computational techniques have proved useful for defining the mutations, genes and molecular networks that drive diverse cancer phenotypes and that determine clonal architectures in tumour samples. Collectively, these tools have advanced the study of genomic, transcriptomic and epigenomic alterations in cancer, and their association to clinical properties. Here, we review cancer genomics software and the insights that have been gained from their application.
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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.