ArticleGenome biology2014
Cancer progression modeling using static sample data.
Article in Genome biology, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 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
14 citing papers in PubMed.
- A pairwise immune gene model for predicting overall survival and stratifying subtypes of colon adenocarcinoma.Journal of cancer research and clinical oncology · 2023Article
- The immune subtypes and landscape of sarcomas.BMC immunology · 2022Article
- Article
- Identification and Validation of Immune Molecular Subtypes and Immune Landscape Based on Colon Cancer Cohort.Frontiers in medicine · 2022Article
- The intra-class heterogeneity of immunophenotyping and immune landscape in oesophageal cancer and clinical implications.Annals of medicine · 2021Article
- Identification of glioblastoma immune subtypes and immune landscape based on a large cohort.Hereditas · 2021Article
- Analysis of Immune Gene Expression Subtypes Reveals Osteosarcoma Immune Heterogeneity.Journal of oncology · 2021Article
- Immune Classification and Immune Landscape Analysis of Triple-Negative Breast Cancer.Frontiers in genetics · 2021Article
- Deep-learning approach to identifying cancer subtypes using high-dimensional genomic data.Bioinformatics (Oxford, England) · 2020Article
- The Immune Subtypes and Landscape of Squamous Cell Carcinoma.Clinical cancer research : an official journal of the American Association for Cancer Research · 2019Article
- Expression-based analyses indicate a central role for hypoxia in driving tumor plasticity through microenvironment remodeling and chromosomal instability.NPJ systems biology and applications · 2018Article
- Principal Graph and Structure Learning Based on Reversed Graph Embedding.IEEE transactions on pattern analysis and machine intelligence · 2017Article
- Inferring clonal structure in HTLV-1-infected individuals: towards bridging the gap between analysis and visualization.Human genomics · 2017Article
- Computational approach for deriving cancer progression roadmaps from static sample data.Nucleic acids research · 2017Article
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
As molecular profiling data continues to accumulate, the design of integrative computational analyses that can provide insights into the dynamic aspects of cancer progression becomes feasible. Here, we present a novel computational method for the construction of cancer progression models based on the analysis of static tumor samples. We demonstrate the reliability of the method with simulated data, and describe the application to breast cancer data. Our findings support a linear, branching model for breast cancer progression. An interactive model facilitates the identification of key molecular events in the advance of disease to malignancy.
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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.