ArticleGenome biology2008
Indirect genomic effects on survival from gene expression data.
Article in Genome biology, 2008. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 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
6 citing papers in PubMed, 10 citations in OpenAlex.
- Lipids in the cell: organisation regulates function.Cellular and molecular life sciences : CMLS · 2018Review
- Principles and methods of integrative genomic analyses in cancer.Nature reviews. Cancer · 2014Review
- Integrative genomics with mediation analysis in a survival context.Computational and mathematical methods in medicine · 2013Article
- Role of plasma phospholipid transfer protein in lipid and lipoprotein metabolism.Biochimica et biophysica acta · 2012Review
- PLTP is present in the nucleus, and its nuclear export is CRM1-dependent.Biochimica et biophysica acta · 2009Article
- Understanding quantitative genetics in the systems biology era.International journal of biological sciences · 2009Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In cancer, genes may have indirect effects on patient survival, mediated through interactions with other genes. Methods to study the indirect effects that contribute significantly to survival are not available. We propose a novel methodology to detect and quantify indirect effects from gene expression data. We discover indirect effects through several target genes of transcription factors in cancer microarray data, pointing to genetic interactions that play a significant role in tumor progression.
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.