ArticleTheoretical biology & medical modelling2008
A statistical model for the identification of genes governing the incidence of cancer with age.
Article in Theoretical biology & medical modelling, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 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.
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Who cites it
5 citing papers in PubMed, 6 citations in OpenAlex.
- Towards a systemic paradigm in carcinogenesis: linking epigenetics and genetics.Molecular biology reports · 2015Article
- A graphical weighted power improving multiplicity correction approach for SNP selections.Current genomics · 2014Article
- Holm multiple correction for large-scale gene-shape association mapping.BMC genetics · 2014Article
- Dynamic modeling of genes controlling cancer stem cell proliferation.Frontiers in genetics · 2012Article
- Do Women Have Equal Chances for an Academic Career in Radiation Oncology in Canada? A Comparison With Related Specialties.Advances in radiation oncologyArticle
Corrections and comments
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Authors and funding
2 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The cancer incidence increases with age. This epidemiological pattern of cancer incidence can be attributed to molecular and cellular processes of individual subjects. Also, the incidence of cancer with ages can be controlled by genes. Here we present a dynamic statistical model for explaining the epidemiological pattern of cancer incidence based on individual genes that regulate cancer formation and progression. We incorporate the mathematical equations of age-specific cancer incidence into a framework for functional mapping aimed at identifying quantitative trait loci (QTLs) for dynamic changes of a complex trait. The mathematical parameters that specify differences in the curve of cancer incidence among QTL genotypes are estimated within the context of maximum likelihood. The model provides testable quantitative hypotheses about the initiation and duration of genetic expression for QTLs involved in cancer progression. Computer simulation was used to examine the statistical behavior of the model. The model can be used as a tool for explaining the epidemiological pattern of cancer incidence.
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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.