ArticleBriefings in bioinformatics2010
Knowledge-based data analysis comes of age.
Article in Briefings in bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers, 1 of them a synthesis that pooled it.
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
9 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- ConReg-R: Extrapolative recalibration of the empirical distribution of p-values to improve false discovery rate estimates.Biology direct · 2011Pooled it
- Application of Multiple Omics to Understand Postoperative Delirium Pathophysiology in Humans.Gerontology · 2023Review
- Explore the Underlying Mechanism Between Atopic Dermatitis and Major Depressive Disorder.Frontiers in genetics · 2021Article
- UGT2B17 and miR-224 contribute to hormone dependency trends in adenocarcinoma and squamous cell carcinoma of esophagus.Bioscience reports · 2019Article
- Knowledge-based compact disease models identify new molecular players contributing to early-stage Alzheimer's disease.BMC systems biology · 2013Article
- Knowledge-based identification of soluble biomarkers: hepatic fibrosis in NAFLD as an example.PloS one · 2013Article
- Leveraging domain information to restructure biological prediction.BMC bioinformatics · 2011Article
- OnionTree XML: a format to exchange gene-related probabilities.Journal of biomolecular structure & dynamics · 2011Article
- Phenomics: the next challenge.Nature reviews. Genetics · 2010Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author at 1 institution in 1 country.
Funding
Abstract
The emergence of high-throughput technologies for measuring biological systems has introduced problems for data interpretation that must be addressed for proper inference. First, analysis techniques need to be matched to the biological system, reflecting in their mathematical structure the underlying behavior being studied. When this is not done, mathematical techniques will generate answers, but the values and reliability estimates may not accurately reflect the biology. Second, analysis approaches must address the vast excess in variables measured (e.g. transcript levels of genes) over the number of samples (e.g. tumors, time points), known as the 'large-p, small-n' problem. In large-p, small-n paradigms, standard statistical techniques generally fail, and computational learning algorithms are prone to overfit the data. Here we review the emergence of techniques that match mathematical structure to the biology, the use of integrated data and prior knowledge to guide statistical analysis, and the recent emergence of analysis approaches utilizing simple biological models. We show that novel biological insights have been gained using these techniques.
Indexed as
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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.