ReviewMolecular cancer2007
In silico gene expression analysis--an overview.
Review in Molecular cancer, 2007. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 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
26 citing papers in PubMed.
- Modeling thoracic aortic genetic variants in the zebrafish: useful for predicting clinical pathogenicity?Frontiers in cardiovascular medicine · 2025Review
- Abiotic Stress Tolerance Boosted by Genetic Diversity in Plants.International journal of molecular sciences · 2024Article
- Pungency related gene network in Allium sativum L., response to sulfur treatments.BMC genomic data · 2024Article
- Benefit of using interaction effects for the analysis of high-dimensional time-response or dose-response data for two-group comparisons.Scientific reports · 2023Article
- Can endocan serve as a molecular "hepatostat" in liver regeneration?Molecular medicine (Cambridge, Mass.) · 2023Article
- Tumor stemness score to estimate epithelial-to-mesenchymal transition (EMT) and cancer stem cells (CSCs) characterization and to predict the prognosis and immunotherapy response in bladder urothelial carcinoma.Stem cell research & therapy · 2023Article
- Three Newly Recognized Likely Pathogenic Gene Variants Associated with Hereditary Transthyretin Amyloidosis.Neurology and therapy · 2022Article
- Article
- REVEL and BayesDel outperform other in silico meta-predictors for clinical variant classification.Scientific reports · 2019Article
- Genome-wide host RNA signatures of infectious diseases: discovery and clinical translation.Immunology · 2018Review
- Electronic Northern Analysis of Genes and Modeling of Gene Networks Underlying Bovine Milk Fat Production.Genetics research international · 2017Article
- A systematic assessment of linking gene expression with genetic variants for prioritizing candidate targets.Pacific Symposium on Biocomputing. Pacific Symposium on Biocomputing · 2015Article
- Oestrogen receptor-mediated expression of Olfactomedin 4 regulates the progression of endometrial adenocarcinoma.Journal of cellular and molecular medicine · 2014Article
- Network-based differential gene expression analysis suggests cell cycle related genes regulated by E2F1 underlie the molecular difference between smoker and non-smoker lung adenocarcinoma.BMC bioinformatics · 2013Article
- Identification and Insilico Analysis of Retinoblastoma Serum microRNA Profile and Gene Targets Towards Prediction of Novel Serum Biomarkers.Bioinformatics and biology insights · 2013Article
- An ovary transcriptome for all maturational stages of the striped bass (Morone saxatilis), a highly advanced perciform fish.BMC research notes · 2012Article
- Correlated tissue expression of genes of cytoplasmic and mitochondrial nucleotide metabolisms in normal tissues is disrupted in transformed tissues.Nucleosides, nucleotides & nucleic acids · 2012Article
- Applications of next generation sequencing in molecular ecology of non-model organisms.Heredity · 2011Review
- Errors in CGAP xProfiler and cDNA DGED: the importance of library parsing and gene selection algorithms.BMC bioinformatics · 2011Article
- hSAGEing: an improved SAGE-based software for identification of human tissue-specific or common tumor markers and suppressors.PloS one · 2010Article
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
No grant is acknowledged in the PubMed record.
Abstract
Efforts aimed at deciphering the molecular basis of complex disease are underpinned by the availability of high throughput strategies for the identification of biomolecules that drive the disease process. The completion of the human genome-sequencing project, coupled to major technological developments, has afforded investigators myriad opportunities for multidimensional analysis of biological systems. Nowhere has this research explosion been more evident than in the field of transcriptomics. Affordable access and availability to the technology that supports such investigations has led to a significant increase in the amount of data generated. As most biological distinctions are now observed at a genomic level, a large amount of expression information is now openly available via public databases. Furthermore, numerous computational based methods have been developed to harness the power of these data. In this review we provide a brief overview of in silico methodologies for the analysis of differential gene expression such as Serial Analysis of Gene Expression and Digital Differential Display. The performance of these strategies, at both an operational and result/output level is assessed and compared. The key considerations that must be made when completing an in silico expression analysis are also presented as a roadmap to facilitate biologists. Furthermore, to highlight the importance of these in silico methodologies in contemporary biomedical research, examples of current studies using these approaches are discussed. The overriding goal of this review is to present the scientific community with a critical overview of these strategies, so that they can be effectively added to the tool box of biomedical researchers focused on identifying the molecular mechanisms of disease.
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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.