ReviewHuman molecular genetics2010
Analysis of next-generation genomic data in cancer: accomplishments and challenges.
Review in Human molecular genetics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 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
68 citing papers in PubMed.
- Exome enrichment and SOLiD sequencing of formalin fixed paraffin embedded (FFPE) prostate cancer tissue.International journal of molecular sciences · 2012Trial
- RD-OMICS: An Integrative Multi-Omics Data Inventory in Rare Diseases.bioRxiv : the preprint server for biology · 2026Article
- The role of advanced diagnostics on precision medicine in hemato oncology.Discover oncology · 2025Review
- Molecular methods in cancer diagnostics: a short review.Annals of medicine · 2024Review
- Resampling and harmonization for mitigation of heterogeneity in image parameters of baseline scans.Scientific reports · 2022Article
- Role of Artificial Intelligence in Radiogenomics for Cancers in the Era of Precision Medicine.Cancers · 2022Review
- Review
- Article
- Radiogenomics in brain, breast, and lung cancer: opportunities and challenges.Journal of medical imaging (Bellingham, Wash.) · 2021Review
- Radiogenomics Based on PET Imaging.Nuclear medicine and molecular imaging · 2020Review
- Comparison of somatic variant detection algorithms using Ion Torrent targeted deep sequencing data.BMC medical genomics · 2019Article
- Inter-organ cross-talk in metabolic syndrome.Nature metabolism · 2019Review
- Article
- Mutations in an Innate Immunity Pathway Are Associated with Poor Overall Survival Outcomes and Hypoxic Signaling in Cancer.Cell reports · 2018Article
- Genomics of adult and pediatric solid tumors.American journal of cancer research · 2018Review
- Pysim-sv: a package for simulating structural variation data with GC-biases.BMC bioinformatics · 2017Article
- Exome Sequencing of Oral Squamous Cell Carcinoma Reveals Molecular Subgroups and Novel Therapeutic Opportunities.Theranostics · 2017Article
- Optimized pipeline of MuTect and GATK tools to improve the detection of somatic single nucleotide polymorphisms in whole-exome sequencing data.BMC bioinformatics · 2016Article
- Aberrant RNA splicing in cancer; expression changes and driver mutations of splicing factor genes.Oncogene · 2016Review
- The State of the Art in Colorectal Cancer Molecular Biomarker Testing.Advances in anatomic pathology · 2016Review
8 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
The application of next-generation sequencing technology has produced a transformation in cancer genomics, generating large data sets that can be analyzed in different ways to answer a multitude of questions about the genomic alterations associated with the disease. Analytical approaches can discover focused mutations such as substitutions and small insertion/deletions, large structural alterations and copy number events. As our capacity to produce such data for multiple cancers of the same type is improving, so are the demands to analyze multiple tumor genomes simultaneously growing. For example, pathway-based analyses that provide the full mutational impact on cellular protein networks and correlation analyses aimed at revealing causal relationships between genomic alterations and clinical presentations are both enabled. As the repertoire of data grows to include mRNA-seq, non-coding RNA-seq and methylation for multiple genomes, our challenge will be to intelligently integrate data types and genomes to produce a coherent picture of the genetic basis of cancer.
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.