ReviewNucleic acids research2016
Discovering and understanding oncogenic gene fusions through data intensive computational approaches.
Review in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 110 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.
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
110 citing papers in PubMed.
- Article
- Comparative genomic analysis reveals spine formation and coral prostaglandin tolerance in crown-of-thorns starfish.Fundamental research · 2026Article
- A subset of high-grade sarcomas with myogenic differentiation are associated with recurrent FGFR fusions.The journal of pathology. Clinical research · 2026Article
- FuDiCo: Gene Fusion-Initiated Path Propagation for Disease Comorbidity Prediction.Current issues in molecular biology · 2026Article
- Article
- ESR1 fusion proteins in breast cancer: distinguishing oncogenic drivers from passenger events.Oncogene · 2026Review
- Genomic Landscape Analysis of Canine Pulmonary Adenocarcinoma Reveals Candidate Targetable Gene Fusions.Veterinary and comparative oncology · 2026Article
- The GF-NEO discovery platform unveils a [KQE][DG] sequence motif within fusion neoantigens in pediatric cancer.iScience · 2026Article
- Systematic fusion transcript discovery in mantle cell lymphoma using long-read sequencing.bioRxiv : the preprint server for biology · 2026Article
- Fusions4U: a resource of validated and annotated gene fusions in 328 cancer cell lines.BMC cancer · 2025Article
- Landscape of gene fusions in hormone receptor-positive breast cancer reveals ADK fusions as drivers of progression and potential therapeutic targets.Cell discovery · 2025Article
- Phase-separating fusion proteins drive cancer by upsetting transcription regulation.Genome biology · 2025Article
- Whole transcriptome analysis identifiesCancer pathogenesis and therapy · 2025Article
- Article
- Combining panel-based and whole-transcriptome-based gene fusion detection by long-read sequencing.Cell reports methods · 2025Article
- Mapping the future: bibliometric analysis of omics research trends in non-small cell lung cancer.Discover oncology · 2025Article
- Evaluating Gene Fusions as Prognostic Biomarkers and Therapeutic Targets in Immune Checkpoint Blockade-Treated Advanced Melanoma: A Retrospective Analysis.Cancer research communications · 2025Article
- Massively parallel immunopeptidome by DNA sequencing provides insights into cancer antigen presentation.Nature genetics · 2025Article
- Characterization of Tumor Antigens from Multi-omics Data: Computational Approaches and Resources.Genomics, proteomics & bioinformatics · 2025Review
- Uncovering the domain language of protein functionality and cell phenotypes using DANSy.bioRxiv : the preprint server for biology · 2025Article
50 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
2 authors.
Funding
Abstract
Although gene fusions have been recognized as important drivers of cancer for decades, our understanding of the prevalence and function of gene fusions has been revolutionized by the rise of next-generation sequencing, advances in bioinformatics theory and an increasing capacity for large-scale computational biology. The computational work on gene fusions has been vastly diverse, and the present state of the literature is fragmented. It will be fruitful to merge three camps of gene fusion bioinformatics that appear to rarely cross over: (i) data-intensive computational work characterizing the molecular biology of gene fusions; (ii) development research on fusion detection tools, candidate fusion prioritization algorithms and dedicated fusion databases and (iii) clinical research that seeks to either therapeutically target fusion transcripts and proteins or leverages advances in detection tools to perform large-scale surveys of gene fusion landscapes in specific cancer types. In this review, we unify these different-yet highly complementary and symbiotic-approaches with the view that increased synergy will catalyze advancements in gene fusion identification, characterization and significance evaluation.
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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.