ArticleBMC bioinformatics2010
Content-based microarray search using differential expression profiles.
Article in BMC bioinformatics, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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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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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.
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Who cites it
22 citing papers in PubMed.
- Vitamin C and N-acetylcysteine promote bovine adipose-derived mesenchymal stem cell proliferation and differentiation via Akt/mTOR/P70S6K signalling pathway for cultured meat production.Animal bioscience · 2025Article
- iModulonMiner and PyModulon: Software for unsupervised mining of gene expression compendia.PLoS computational biology · 2024Article
- Connecting omics signatures and revealing biological mechanisms with iLINCS.Nature communications · 2022Article
- Perturbations in neuroinflammatory pathways are associated with paclitaxel-induced peripheral neuropathy in breast cancer survivors.Journal of neuroimmunology · 2019Article
- Differential expression of genes and differentially perturbed pathways associated with very high evening fatigue in oncology patients receiving chemotherapy.Supportive care in cancer : official journal of the Multinational Association of Supportive Care in Cancer · 2018Article
- Computational Drug Target Screening through Protein Interaction Profiles.Scientific reports · 2016Article
- Gene Expression Profiling of Evening Fatigue in Women Undergoing Chemotherapy for Breast Cancer.Biological research for nursing · 2016Article
- GEMINI: a computationally-efficient search engine for large gene expression datasets.BMC bioinformatics · 2016Article
- Leveraging 3D chemical similarity, target and phenotypic data in the identification of drug-protein and drug-adverse effect associations.Journal of cheminformatics · 2016Article
- REDD1 functions at the crossroads between the therapeutic and adverse effects of topical glucocorticoids.EMBO molecular medicine · 2015Article
- GESearch: An Interactive GUI Tool for Identifying Gene Expression Signature.BioMed research international · 2015Article
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- Drug similarity search based on combined signatures in gene expression profiles.Healthcare informatics research · 2014Article
- Pathprinting: An integrative approach to understand the functional basis of disease.Genome medicine · 2013Article
- Identifying genes relevant to specific biological conditions in time course microarray experiments.PloS one · 2013Article
- Direct integration of intensity-level data from Affymetrix and Illumina microarrays improves statistical power for robust reanalysis.BMC medical genomics · 2012Article
- A systems biology approach to the global analysis of transcription factors in colorectal cancer.BMC cancer · 2012Article
- Deriving transcriptional programs and functional processes from gene expression databases.Bioinformatics (Oxford, England) · 2012Article
- Data-driven information retrieval in heterogeneous collections of transcriptomics data links SIM2s to malignant pleural mesothelioma.Bioinformatics (Oxford, England) · 2012Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
backgroundWith the expansion of public repositories such as the Gene Expression Omnibus (GEO), we are rapidly cataloging cellular transcriptional responses to diverse experimental conditions. Methods that query these repositories based on gene expression content, rather than textual annotations, may enable more effective experiment retrieval as well as the discovery of novel associations between drugs, diseases, and other perturbations.
resultsWe develop methods to retrieve gene expression experiments that differentially express the same transcriptional programs as a query experiment. Avoiding thresholds, we generate differential expression profiles that include a score for each gene measured in an experiment. We use existing and novel dimension reduction and correlation measures to rank relevant experiments in an entirely data-driven manner, allowing emergent features of the data to drive the results. A combination of matrix decomposition and p-weighted Pearson correlation proves the most suitable for comparing differential expression profiles. We apply this method to index all GEO DataSets, and demonstrate the utility of our approach by identifying pathways and conditions relevant to transcription factors Nanog and FoxO3.
conclusionsContent-based gene expression search generates relevant hypotheses for biological inquiry. Experiments across platforms, tissue types, and protocols inform the analysis of new datasets.
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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.