ArticleBiology2012
Biomarker gene signature discovery integrating network knowledge.
Article in Biology, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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
11 citing papers in PubMed.
- 3PNMF-MKL: A non-negative matrix factorization-based multiple kernel learning method for multi-modal data integration and its application to gene signature detection.Frontiers in genetics · 2023Article
- Feature selection and classification over the network with missing node observations.Statistics in medicine · 2022Article
- Advancing translational research in neuroscience through multi-task learning.Frontiers in psychiatry · 2022Review
- Particle swarm optimization artificial intelligence technique for gene signature discovery in transcriptomic cohorts.Computational and structural biotechnology journal · 2022Article
- Graph-based exploitation of gene ontology using GOxploreR for scrutinizing biological significance.Scientific reports · 2020Article
- From hype to reality: data science enabling personalized medicine.BMC medicine · 2018Article
- Patients with early-stage oropharyngeal cancer can be identified with label-free serum proteomics.British journal of cancer · 2018Article
- Comparative network stratification analysis for identifying functional interpretable network biomarkers.BMC bioinformatics · 2017Article
- Identifying module biomarker in type 2 diabetes mellitus by discriminative area of functional activity.BMC bioinformatics · 2015Article
- Network and data integration for biomarker signature discovery via network smoothed T-statistics.PloS one · 2013Article
- Cancer Progression Prediction Using Gene Interaction Regularized Elastic Net.IEEE/ACM transactions on computational biology and bioinformaticsArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Discovery of prognostic and diagnostic biomarker gene signatures for diseases, such as cancer, is seen as a major step towards a better personalized medicine. During the last decade various methods, mainly coming from the machine learning or statistical domain, have been proposed for that purpose. However, one important obstacle for making gene signatures a standard tool in clinical diagnosis is the typical low reproducibility of these signatures combined with the difficulty to achieve a clear biological interpretation. For that purpose in the last years there has been a growing interest in approaches that try to integrate information from molecular interaction networks. Here we review the current state of research in this field by giving an overview about so-far proposed approaches.
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.